iOS/Android template fails to run due to error: no such module 'shared'

Describe the bug
I downloaded the iOS/Android template repo and can successfully build for android. iOS on the other hand is returning:
/Projects/compose-multiplatform-ios-android-template/iosApp/iosApp/ContentView.swift:3:8: error: no such module 'shared'
import shared

My version of cocoapods is 1.12.1 and I installed it via brew at /opt/homebrew/bin/pod
Affected platforms
Select one of the platforms below:

iOS

Versions

Kotlin version*: 1.8.20
Compose Multiplatform version*: 1.4.0
OS version(s)* (required for Desktop and iOS issues): Ventura 13.1
OS architecture (x86 or arm64): arm64
JDK (for desktop issues):
java 19 2022-09-20
Java(TM) SE Runtime Environment (build 19+36-2238)
Java HotSpot(TM) 64-Bit Server VM (build 19+36-2238, mixed mode, sharing)

To Reproduce
Steps and/or the code snippet to reproduce the behavior:

Open Edit Configurations -> ios Application -> iosApp
Choose iosApp/iosApp.xcodeproj as the Xcode Project FIle -> Apply -> OK
Run iosApp
See error

After this I also tried:
cd iosApp
pod cache clean --all
pod install

Then I tried deleting all the build folders, building the android app first, then iOS. No matter what I do or what order I try it, I get this error.
Expected behavior
The iOS simulator should open up a virtual iPhone with the template app, aka no build errors.
Screenshots
If applicable, add screenshots to help explain your problem.
Additional context
Sometimes, rather than the error being re: shared it is that Main_iosKt doesn't exist in the space... which is an error I see in some recently closed issues for this project. The only problem is the "fix" was to run something that is supposed to work for iOS, which I am currently doing.

After restarting my computer, the error is now the missing Main_iosKt one:
/Projects/compose-multiplatform-ios-android-template/iosApp/iosApp/ContentView.swift:7:9: error: cannot find 'Main_iosKt' in scope
        Main_iosKt.MainViewController()

Where is it even defined that the name of the package should be "Main_iosKt"? Is that just what main.ios.kt gets converted to under the hood? Either way, any help would be appreciated.

Hey @tahoeschrader,
I think you missed the following steps:
https://kotlinlang.org/docs/multiplatform-mobile-integrate-in-existing-app.html#create-an-ios-project-in-xcode

Hey @tahoeschrader,
I think you missed the following steps:
https://kotlinlang.org/docs/multiplatform-mobile-integrate-in-existing-app.html#create-an-ios-project-in-xcode

Hm, I see. A lot of documentation I've found online imply xcode will be called from Android Studio via the cli though. Especially considering this official template already has the xcode project files and whatnot already included.
I was under the impression i'd only need to do the step you're linking for a brand new multiplatform project id be writing from scratch without building off this template.

I have experience this error using the project template after corrupting the gradle.
I recommend you to re-download the gradle by removing the current caches
rm -rf ~/.gradle/caches/

Now its is fixed if you using Kotlin Multiplatform Wizard: https://kmp.jetbrains.com/?_gl=11ds9oqm_gaMzUzNzc0NzEuMTY5MjYxMjIxMA.._ga_9J976DJZ68*MTY5OTAxNTg2NC4yMC4xLjE2OTkwMTc3MzcuMC4wLjA.&_ga=2.23061945.388460062.1699015864-35377471.1692612210
When open iosApp as Xcode project, make sure that you first build it in Android Studio, and then also build in Xcode, that any errors of Xcode project must not appear and u can run project on any of you devices!

Please check the following ticket on YouTrack for follow-ups to this issue. GitHub issues will be closed in the coming weeks.


(fix): refactor for unicorn threads

Summary

Refactor to sleep remaining time before flush.
break out process events

Test plan
Pass all existing tests
Issues

Coverage decreased (-0.005%) to 99.542% when pulling bdb018daf239bea62eab7748e02a7152ecf81aea on refactorForUnicorn into c83512857d4bee020bdb897ec6cc82509629c474 on master.

@thomaszurkan-optimizely  As per docs, the Queue class implements locking mechanism internally. Aren't we doing same as what event_queue.pop in blocking mode would do? That is suspend the thread.

@oakbani the queue class does have a lock but no timeout.  so, if no other event came the queue would never be flushed on timeout interval.


Parser does not support Fn::GetAtt dot notation shorthand

https://twitter.com/SeanTylerMyers/status/1525305955583307777

CFN unique parsing find today: "Fn::GetAtt" has a shorthand in YAML that actually works in JSON as well, so {"Fn::GetAtt": "IamRole.Arn"} is valid.

Hey Momo,
Just trying to get some clarity, do we plan to support {"Fn::GetAtt": "logicalNameOfResource.attributeName"} even this is not documented in CFN docs, is this for compatibility purpose?

@lejiati Good question! I think we can make a decision on this. It's definitely a "nice to have" hence, the p2 label.
It came up in discussions between @rix0rrr @otaviomacedo and me, looking at what other CFN parsers (including the one in CDK) are already supporting. Issue was mainly intended as a reminder of this. I'll make sure to make this clearer next time.


feat: sort knn node ids before getting into TakeExec

Could you run the benchmark suite for ANN/KNN search and show the changes from main?

Close this. THe design is not good to have consistent improvement cross the board.


Understanding MassTransit -> Saga documentaiton seem outdated

Some of the documentation seems to be OK there although it somewhat duplicates the Saga page.
However, the example code here http://docs.masstransit-project.com/en/latest/overview/saga.html#subscribing-to-the-saga is definitely not V3 API.

Yikes, that is old.

This was completely rewritten.


Broken in IE11 due to missing Object.assign

Commit 464af403aec464d2428220288960f6b16e01c34a by @jquense completely breaks IE11 due to removal of babel-plugin-object-assign.
Please re-add the polyfill for Object.assign and also consider fixing #464, which is another show-stopper for IE11. Thanks!

this would be nice!

This should be fixed by https://github.com/intljusticemission/react-big-calendar/pull/542.


Create example data for MaterialProcessing Subclasses

A running issue until all MaterialProcessing Subclasses have an example data set committed for them:

[x] SubsamplingProcess
[x] MixingProcess
[x] FiltrationProcess
[x] PhaseSeparationProcess
[ ] AcidificationProcess
[ ] AnalyteStorage
[x] ExtractionProcess
[ ] ReactionActivity
[ ] SievingProcess
[ ] SampleDrying
[ ] DerivatizationProcess
[ ] ChemicalReactionProcess
[ ] PhMeasuringProcess
[ ] DissolvingProcess

Thanks @anastasiyaprymolenna . Please provide the name of the example data file for each of those classes that you have checked off as complete.

branch for committing to https://github.com/microbiomedata/nmdc-schema/tree/1328-create-example-data-for-materialprocessing-subclasses

Subsampling https://github.com/microbiomedata/nmdc-schema/blob/1328-create-example-data-for-materialprocessing-subclasses/src/data/valid/MixingProcess-Biosample-input.yaml

Mixing  https://github.com/microbiomedata/nmdc-schema/blob/1328-create-example-data-for-materialprocessing-subclasses/src/data/valid/MixingProcess-Biosample-input.yaml

Filtration:
Valid: https://github.com/microbiomedata/nmdc-schema/blob/1328-create-example-data-for-materialprocessing-subclasses/src/data/valid/FiltrationProcess-Biosample-input.yaml
Invalid: https://github.com/microbiomedata/nmdc-schema/blob/1328-create-example-data-for-materialprocessing-subclasses/src/data/invalid/FiltrationProcess-Biosample-input.yaml

PhaseSeparation:
https://github.com/microbiomedata/nmdc-schema/blob/1328-create-example-data-for-materialprocessing-subclasses/src/data/valid/PhaseSeparationProcess-Biosample-input.yaml

Filtration and Phase separation need to be reviewed and updated when the models are finalized, this example data will not currently validate

Extraction examples
https://github.com/microbiomedata/nmdc-schema/blob/main/src/data/valid/Extraction-NEON.yaml
https://github.com/microbiomedata/nmdc-schema/blob/main/src/data/valid/Extraction-metabolomics.yaml
https://github.com/microbiomedata/nmdc-schema/blob/main/src/data/valid/Extraction-proteomics.yaml

@anastasiyaprymolenna @JamesTessmer do we have a status update? Can any more of these be checked off?
What is feasible to get done for the berk roll out?

DissolvingProcess valid:
https://github.com/microbiomedata/berkeley-schema-fy24/blob/main/src/data/valid/DissolvingProcess-minimal.yaml
ChemicalConversionProcess
https://github.com/microbiomedata/berkeley-schema-fy24/blob/main/src/data/valid/ChemicalConversionProcess-minimal.yaml
https://github.com/microbiomedata/berkeley-schema-fy24/blob/main/src/data/valid/ChemicalConversionProcess-digest.yaml
StorageProcess
https://github.com/microbiomedata/berkeley-schema-fy24/blob/main/src/data/valid/StorageProcess-minimal.yaml

@mslarae13 Since opening the issue we have removed the need for some classes, so I crossed those out, but the rest of the new MaterialProcessing subclasses all have data examples created for them. I will close this issue.


Download link is wrong

The download link in the README.md points to CDNJS and not Go Alfred.

Fixed by 7d06a60


[ST-796] Introduce logging logger and print audit log

abstract
I introduced a logger used by logging and set log levels default and audit. add a global option --log-level to change level for printing logs. when we only set the log level, the logger print log.
I'd like to replace the @command.echo log output with this logger in the future.
example
when we set log-level, logs are printed like below,
$ LAUNCHABLE_TOKEN=XXX launchable --log-level audit subset --build sample-1  --target 10% maven ./src/test/java/com/example/app/App*
AUDIT:launchable:send request method:post path:/intake/organizations/<ORG>/workspaces/<WORKSPACE>/builds/sample-1/test_sessions headers:{'Content-Type': 'application/json'} args:{'timeout': (5, 60)}
AUDIT:launchable:send request method:post path:/intake/organizations/<ORG>/workspaces/<WORKSPACE>/subset headers:{'Content-Type': 'application/json', 'Content-Encoding': 'gzip'} args:{'data': b'\x1f\x8b\x08\x00C^3`\x02\xff\xabV*I-.\tH,\xc9(V\xb2R\x88\x8e\xd5QP*I,JO-\x01\xf2\x0c\xf4\x0c\x81\xdc\xe2\xd4\xe2\xe2\xcc\xfc< \xbfZ)3\x05H)\x19\x9b+\xd5\xd6\x02\x00\xd1bG\xaa9\x00\x00\x00', 'timeout': (5, 180)}

about log level
I was going to set the highest level to the audit log level. However, when I use some times, I found it a little noisy that if we set the error to log level, the audit logs were printed.
Also, when we want to show the audit logs, there weren't any errors usually. so error log level and audit log level behavior don't conflict.
So I changed log levels from audit>critical>error>warn>info>debug to critical>error>warn>audit>info>debug.

🤔 🤔 🤔
$ pipenv run test tests/utils/test_logger.py
..
----------------------------------------------------------------------
Ran 2 tests in 0.001s

OK

$ pipenv run test
...............................b'Hello world'
.F.
======================================================================
FAIL: test_log_level_audit (tests.utils.test_logger.LoggerTest)
----------------------------------------------------------------------
Traceback (most recent call last):
  File<EMAIL_ADDRESS>line 1337, in patched
    return func(*newargs, **newkeywargs)
  File "/Users/yabuki-ryosuke/src/github.com/launchableinc/cli/tests/utils/test_logger.py", line 31, in test_log_level_audit
    self.assertEqual(stderr.getvalue(
AssertionError: '' != 'AUDIT:launchable:audit\nCRITICAL:launchab[58 chars]rn\n'
+ AUDIT:launchable:audit
+ CRITICAL:launchable:critical
+ ERROR:launchable:error
+ WARNING:launchable:warn

----------------------------------------------------------------------
Ran 34 tests in 0.303s

FAILED (failures=1)

I left one comment. All others look good.


Allow for one way connected lists

It should be allowed to connect listA with listB without connecting listB with listA.
This means the user can move an item from listA to listB but not back.
This can be useful if cloning is added (e.g. have a list where items can be dragged out (but will not be removed) and added to another list)

This has been fixed in #295


drop does not delete a bcolz directory

Calling drop on an existing bcolz data directory results in an RuntimeError:
bcolz/carray_ext.pyx in bcolz.carray_ext.carray.flush (bcolz/carray_ext.c:31412)()
bcolz/carray_ext.pyx in bcolz.carray_ext.chunk.cinit (bcolz/carray_ext.c:4279)()
bcolz/carray_ext.pyx in bcolz.carray_ext.chunk.compress_data (bcolz/carray_ext.c:5222)()
RuntimeError: fatal error during Blosc compression: -1

drop is kind of a weird function because it works on strings which then dispatches to resource which then tries to create it or return the existing thing so it will try to create an empty bcolz array without any type information

Arguably resource is the odd duck here.  It currently serves double duty as "get me the thing corresponding to this string" and "create the thing according to this string.  Arguably this could be split?

yes

we are discussing on gitter

well actually i don't think that resource is odd

i think drop calling resource without knowing anything about whether the thing exists or not is odd

hm, let me think about this


chore: improve documentation around configuration issues

Do we need to open a PR against zed repo to make this visible?

Sadly this is not visible anywhere in zed yet. Its just the Github link in the ui, which points to this repo directly. So should be fine for now.


Horizontal regions frontend fix

Description
Instead of returning a List[gt_ir.ComputationBlock] (one for each region at the top level), return a gt_ir.ComputeBlock with multiple gt_ir.HorizontalIf Stmts.

@tehrengruber - this corrects a bug that was introduced when we merged the frontend changes for horizontal regions. It's necessary to get the with blocks parsed as a single gt_ir.ComputationBlock so that the overlapping interval check works as intended.


Fixes for Safari on macOS

Remove grid from the app layout
Override the visually-hidden 'Support links' heading in the footer which fixes an issues with Safari scrolling past the end of the page.

Fixes #373 and #374

You can preview this change here:
Built with commit c2fa679359f2b5d439a028cea95ef087854d13b4
https://deploy-preview-382--govuk-design-system-preview.netlify.com


Scrollable dropdown

Suggestion:-
It would be good if have a scrollable dropdown instead of the normal one  for target language, versification scheme, Licence, App Language.
dropdown in use-

suggesiton:-

Joel also use full names in the drop down


kubectl plugin implementation and distribution

we think the easiest way installing and using that tool use with as a kubectl plugin.
we can share ntop with a kubectl plugin we should find a way releasing our tool with a kubectl plugin.
refs.
https://krew.sigs.k8s.io/docs/developer-guide/develop/plugin-development/
https://krew.sigs.k8s.io/docs/developer-guide/distributing-with-krew/

Krew plugin support should added 0.3.0 milestone. It will be our main package distribution way for general use.


Allow renaming of sheet

Received XDTS files often do not have proper sheet names
Can we have an option to choose default sheet name or rename on import in the script panel?

Renaming of sheet is in regards to how the precomp  and folder is imported into AE

By default the script names the precomp and folder containing image sequence what ever the sheet name was for the xdts file. It's almost always never named or checked so having an option to decide the name of the precomp/folder would really help with organization
- GreenBlueClouds

Implemented in 80172a8
Checkbox will enable a textbox in which the import can be renamed as


Improve vanilla mechanics of phantoms

Phantoms are invented by the authors of the game so that they will spawn near the players who do not sleep N of time, but they attack not these players, and all in a row - is it possible to fix it? so that phantom attacked only that player, because of whom spawned

I already did this a long time ago and sent it to Paper. It is the default behavior of phantoms to ignore players that have not slept (insomniacs) or are in creative mode.
You can find these settings in paper.yml (defaulted to true)
https://github.com/PaperMC/Paper/blob/master/Spigot-Server-Patches/0458-Add-phantom-creative-and-insomniac-controls.patch

I already did this a long time ago and sent it to Paper. It is the default behavior of phantoms to ignore players that have not slept (insomniacs) or are in creative mode.
You can find these settings in paper.yml (defaulted to true)
https://github.com/PaperMC/Paper/blob/master/Spigot-Server-Patches/0458-Add-phantom-creative-and-insomniac-controls.patch

so, on the contrary, I meant that they only attacked non-sleeping  (insomniacs), and not everyone who is near them


spring cloud config bus-refresh not working

I play with spring cloud config 2.1.0 and I dont see endpoint bus-refresh when start application.
I only see endpoint bus-env, so I can't refresh my service.
2019-04-24 10:26:53.633  WARN [haft-config,,,] 30356 --- [           main] o.s.boot.actuate.endpoint.EndpointId     : Endpoint ID 'bus-env' contains invalid characters, please migrate to a valid format. 2019-04-24 10:26:53.824  WARN [haft-config,,,] 30356 --- [           main] o.s.boot.actuate.endpoint.EndpointId     : Endpoint ID 'service-registry' contains invalid characters, please migrate to a valid format.
Here my config
`server:
port: 8888
eureka:
instance:
prefer-ip-address: true
client:
service-url:
defaultZone: http://haft:haft123@haft-eureka:8761/eureka/
spring:
application:
name: @artifactId@
cloud:
stream:
bindings:
springCloudBusInput:
destination: config-bus
group: haft-config
springCloudBusOutput:
destination: config-bus
config:
retry:
initial-interval: 3000
multiplier: 1.5
max-interval: 20000
max-attempts: 6
server:
native:
search-locations: file:///E:/scanner_center/SVN/config-repos/development
management:
endpoint:
health:
show-details: always
bus-refresh:
enabled: true
endpoints:
web:
exposure:
exclude: bus-refresh
`
Here my pom:
<dependency> 			<groupId>org.springframework.cloud</groupId> 			<artifactId>spring-cloud-config-server</artifactId> 		</dependency> 		<dependency> 			<groupId>vn.com.hafintech</groupId> 			<artifactId>haft-common-slf4j</artifactId> 		</dependency> 		<dependency> 			<groupId>org.springframework.cloud</groupId> 			<artifactId>spring-cloud-config-monitor</artifactId> 		</dependency> 		<dependency> 			<groupId>org.springframework.cloud</groupId> 			<artifactId>spring-cloud-starter-stream-rabbit</artifactId> 		</dependency> 		<dependency> 			<groupId>vn.com.hafintech</groupId> 			<artifactId>haft-common-web</artifactId> 		</dependency>
Can you help me? Thank you so much.

Please learn how to format code on GitHub.
Why are you excluding the endpoint?
management:
    endpoint:
       health:
          show-details: always
        bus-refresh:
           enabled: true
     endpoints:
           web:
                 exposure:
                     exclude: bus-refresh

explode interface /actuator/bus-refresh?

That is a warning, what is actually not working?

If you would like us to look at this issue, please provide the requested information. If the information is not provided within the next 7 days this issue will be closed.

Closing due to lack of requested feedback. If you would like us to look at this issue, please provide the requested information and we will re-open the issue.


just moving large zip files between drives

Explain the bug
Write a clear description of what the bug is.
To reproduce

Go to '....'
Click on '....'
Scroll down to '....'
See the error

Expected behavior
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Logfile
Upload the log file here for us to understand your issue better.

You can access it from Settings->About->Open log location.
or
Copy the debug.log and debug_fulltrust.log from the following directory, and upload the files here.
%localappdata%\Packages\49306atecsolution.FilesUWP_et10x9a9vyk8t\LocalState

Screenshots
Add screenshots to help explain your problem if needed.
System Information

OS Version: [e.g. Windows 10 20H2 19042.804] (Press WIN + PAUSE/BREAK, use the copy button at the bottom)
App version: [e.g. v1.0] (In the app, go to Settings -> About, the version is shown at the top)

Additional comment
Add any other comment about the problem here. Does this problem happen again after restarting the app?

drag and drop . everything fine, moved multiple files prior no problem . halfway through move OOPS! one of two window closes and window pops up with OH SH!T message I couldn't read quickly enough.  win10 rog strix

@Seneschie We need a little more information from you in order to investigate this issue, please reopen this issue once you have filled out the issue template.


chore(docs) : readme update

update import theme in readme from yml to toml

@chrisduerr for the issue https://github.com/alacritty/alacritty-theme/issues/38 i did update only the readme to provide import for toml


fix loading dashboards from server

fix: url for getting dashboards (double slash)
fix if/else with alerts / dashboards
fix some confusion between object and object UID

rebased on main


RCBlockNumberProviderOf returns different values for relay chain block number if the parachain is spawned from chainspec or via rpc node

Noticed a strange behaviour when testing a runtime migration with chopsticks.
I was testing the runtime upgrade enabling coretime on Polkadot. It involves sending of XCM messages from Polkadot relay chain to Coretime relay chain.
One particular message is SetLease which is handled here. Note the ensure line which compares until with Self::current_timeslice() which is implemented here. let latest = RCBlockNumberProviderOf::<T::Coretime>::current_block_number(); is supposed to fetch the current block number of the relay chain.
At this point I get different values for current_block_number depending on if I run the coretime chain from a chainspec or against an actual RPC node. In the former case I get 1004 while at the latter - 22572435. In both cases the relay chain configuration of chopsticks has block: 22572434 so I expect in both cases current_timeslice() to return 22572435 (one block after the runtime upgrade.
Is there a reason for this behaviour which I don't see?
How to recreate
Recreating the issue is a bit tedious because it requires modified coretime runtime with sp-debug-derive enabled and an additional trace line here.
I've prepared a docker-compose setup here -> https://github.com/tdimitrov/polkadot-coretime-launch-test/tree/post-migration
I'll attach the two binaries (relay chain wasm with the coretime migration and modified coretime wasm) to the issue.

artefacts.zip

Not sure what's the best way to solve this but here is what happened:
When creating the validation data inherent, Chopsticks will try to fetch the parent one and use it as the starting point. So it kinda works for chain with RPC endpoint.
However, when created from chain spec file, there is no parent block, so a hardcoded one is used: https://github.com/AcalaNetwork/chopsticks/blob/29e5a78cc20ddd1a1edae4a1c28c8888a6e03b61/packages/core/src/blockchain/inherent/parachain/validation-data.ts#L23-L25
and then the relaychain block number value is incremented https://github.com/AcalaNetwork/chopsticks/blob/29e5a78cc20ddd1a1edae4a1c28c8888a6e03b61/packages/core/src/blockchain/inherent/parachain/validation-data.ts#L290
The thing is, for Chopsticks, every chain are independent. Even if they are connected via XCM, Chopsticks only forward the messages to the other chain. But the validation data are not actually using the value from relaychain (because in many cases, there is no relaychain being simulated).

I see, thanks @xlc

So it kinda works for chain with RPC endpoint.

Can you elaborate on this? Why 'kinda works'? Any potential pitfalls one needs to know about?

for RPC networks, the parent block will be a real block that contains real relaychain block height. if both relaychain and parachain are using rpc endpoints with latest block, it will work as expected

One thing we could do is add a new parameter to dev_newBlock to specify the relaychain block height to give you more control of it

One thing we could do is add a new parameter to dev_newBlock to specify the relaychain block height to give you more control of it

This will be useful but probably easy to look over. Do you see a benefit in making it a required parameter if a chain is spawned from a chainspec?

it is not used most of the time so no it shouldn't be a required parameter

I agree it's not used most of the time, but if not used it might yield unexpected data which might bite the user badly.
Bottom line it's up to you. Being able to override this value is more than fine for me.


WFLY-17159 Upgrade Infinispan to 14.0.1.Final

Just to kick off some runs with a checkstyle fix.

Thanks for kicking off tests for this branch.  The only relevant failures it found are here:
https://ci.wildfly.org/buildConfiguration/WF_PullRequest_LinuxJdk17/331567?hideProblemsFromDependencies=false&hideTestsFromDependencies=false&expandBuildChangesSection=true&expandBuildTestsSection=true
... for which I created https://github.com/wildfly/wildfly/pull/16196
Closing in favor of https://github.com/wildfly/wildfly/pull/16185


Muti-class segmentation

Thank you for sharing your great work!
Have you tried using SAM-Med3D for multi-class segmentation, such as multi-organ segmentation or something like it?
I'm trying to do it using BraT20 dataset for Brain Tumor Segentation, but it seems like SAM-Med3D is easily influenced by the background class. Specifically, the first class of the mask tokens in the mask-decoder is significantly large.
Do you have any clue about this problem?

Hi, since SAM-Med3D doesn't actually support multi-class seg. Plz clarify your setting. For example, do you use it multiple times with different prompt points to get different output the multiple organs?
BTW, since BraTS is tumor seg dataset, where the target is relatively small, it's reasonable that it is refluenced by the background class.

I only use one point in your source code as the input of the Prompt Encoder, and modify four MLPs. Specifically, I replace the output_hypernetworks_mlps in the Mask Decoder with new MLPs, so that the four masks output by the Mask Decoder correspond to the masks of four different classes.

It seems that you made structural modifications and then conducted experiments under the changed settings. Since I haven't conducted this kind of experiment, I'm afraid I won't be able to give useful suggestions. If you want a detailed discussion, you can present specific results or start a discussion for this repository. Or you can just close this issue. Thx.


can not run elyra example by pipeline

hi,
I installed kubeflow and minio on my server. I also installed elyra in my jupyter lab dockerfile. When I tried the case in elyra, I could run it locally, but when I tried to use the kubeflow pipeline, it shows an error.

i want to know how to fix this problem.
thank you

Hi @ jeff900911,
Can you please provide the following additional information:

which version of Elyra (pip freeze | grep elyra) have you installed?
which version of kubeflow are you using?
what output is displayed in the JupyterLab log/console?

Hi @ jeff900911,
Can you please provide the following additional information:

which version of Elyra (pip freeze | grep elyra) have you installed?
which version of kubeflow are you using?
what output is displayed in the JupyterLab log/console?

Hi @jeff900911,
Can you please provide the following additional information:

which version of Elyra (pip freeze | grep elyra) have you installed?
which version of kubeflow are you using?
what output is displayed in the JupyterLab log/console?

hi @ptitzler
the version of Elyra i have installed is 1.5.3
the kubeflow is 1.0
And could you teach how to check the JupyterLab log, i used kubeflow notebook servers to run my  jupyter lab image. I tried to used the (jupyter notebook --debug > log.file 2>&1), i am not sure whether is correct.  And the logfile shows like the following:

thank you

Hi @jeff900911,
Can you please provide the following additional information:

which version of Elyra (pip freeze | grep elyra) have you installed?
which version of kubeflow are you using?
what output is displayed in the JupyterLab log/console?

hi @ptitzler
the version of Elyra i have installed is 1.5.3
the kubeflow is 1.0
And could you teach how to check the JupyterLab log, i used kubeflow notebook servers to run my  jupyter lab image. I tried to used the (jupyter notebook --debug > log.file 2>&1), i am not sure whether is correct.  And the logfile shows like the following:

thank you

Ah yes, so you've created a Notebook Server  as described in https://v1-0-branch.kubeflow.org/docs/notebooks/setup/ and specified a custom container image? If that's the case, can you please share the image's Dockerfile?
I know @lresende has been looking into this type of deployment in the past.
I don't have access to such a configuration but it is my understanding that you should be able to access the JupyterLab log file using kubectl logs -n kubeflow pod/XXX replacing XXX with the server's pod name.

Ah yes, so you've created a Notebook Server  as described in https://v1-0-branch.kubeflow.org/docs/notebooks/setup/ and specified a custom container image? If that's the case, can you please share the image's Dockerfile?
I know @lresende has been looking into this type of deployment in the past.
I don't have access to such a configuration but it is my understanding that you should be able to access the JupyterLab log file using kubectl logs -n kubeflow pod/XXX replacing XXX with the server's pod name.

Ah yes, so you've created a Notebook Server as described in https://v1-0-branch.kubeflow.org/docs/notebooks/setup/ and specified a custom container image? If that's the case, can you please share the image's Dockerfile?
I know @lresende has been looking into this type of deployment in the past.
I don't have access to such a configuration but it is my understanding that you should be able to access the JupyterLab log file using kubectl logs -n kubeflow pod/XXX replacing XXX with the server's pod name.

hi @ptitzler
i can share my dockerfile:
FROM debian:latest

ENV LANG=C.UTF-8 LC_ALL=C.UTF-8
ENV PATH /opt/conda/bin:$PATH
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update --fix-missing && apt-get install -y wget bzip2 ca-certificates \
    libglib2.0-0 libxext6 libsm6 libxrender1 \
    git mercurial subversion

RUN wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2020.07-Linux-x86_64.sh  -O ~/anaconda.sh && \
    /bin/bash ~/anaconda.sh -b -p /opt/conda && \
    rm ~/anaconda.sh && \
    ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh && \
    echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc && \
    echo "conda activate base" >> ~/.bashrc

RUN apt-get install -y curl grep sed dpkg && \
    TINI_VERSION=`curl https://github.com/krallin/tini/releases/latest | grep -o "/v.*\"" | sed 's:^..\(.*\).$:\1:'` && \
    curl -L "https://github.com/krallin/tini/releases/download/v${TINI_VERSION}/tini_${TINI_VERSION}.deb" > tini.deb && \
    dpkg -i tini.deb && \
    rm tini.deb && \
    apt-get clean

RUN conda install tensorflow \
    && conda install keras -y \
    && pip install cryptography -i https://pypi.tuna.tsinghua.edu.cn/simple \
    && pip install pandas -i https://pypi.tuna.tsinghua.edu.cn/simple \
    && pip install seaborn -i https://pypi.tuna.tsinghua.edu.cn/simple \
    && pip install scikit-learn -i https://pypi.tuna.tsinghua.edu.cn/simple \
    && pip install matplotlib -i https://pypi.tuna.tsinghua.edu.cn/simple \
    && pip install jieba -i https://pypi.tuna.tsinghua.edu.cn/simple

RUN conda install -c conda-forge/label/cf202003 nodejs
RUN pip install --upgrade "elyra<2.0.0" && jupyter lab build

WORKDIR /home/jovyan

USER root

ARG NB_USER=jovyan

EXPOSE 8888

ENV NB_USER $NB_USER
ENV NB_UID=1000
ENV HOME /home/$NB_USER

ENV NB_PREFIX /

CMD ["sh","-c", "jupyter lab --notebook-dir=/home/jovyan --ip=<IP_ADDRESS> --no-browser --allow-root --port=8888 --NotebookApp.token='' --NotebookApp.password='' --NotebookApp.allow_origin='*' --NotebookApp.base_url=${NB_PREFIX}"]

and the following is the logs in pod:
[I 01:57:37.169 LabApp] Saving file at /hello_world_kubeflow_pipelines.pipeline
[W 01:57:37.871 LabApp] Notebook load_data.ipynb is not trusted
[W 01:57:37.952 LabApp] Notebook Part 1 - Data Cleaning.ipynb is not trusted
[I 01:57:43.048 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743' - submitting pipeline
[I 01:57:43.060 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743' - processing pipeline dependencies to: http://<IP_ADDRESS>:9000/ bucket: test folder: hello_world_kubeflow_pipelines-0120015743
/opt/conda/lib/python3.8/site-packages/kfp/dsl/_container_op.py:1021: FutureWarning: Please create reusable components instead of constructing ContainerOp instances directly. Reusable components are shareable, portable and have compatibility and support guarantees. Please see the documentation: https://www.kubeflow.org/docs/pipelines/sdk/component-development/#writing-your-component-definition-file The components can be created manually (or, in case of python, using kfp.components.create_component_from_func or func_to_container_op) and then loaded using kfp.components.load_component_from_file, load_component_from_uri or load_component_from_text: https://kubeflow-pipelines.readthedocs.io/en/stable/source/kfp.components.html#kfp.components.load_component_from_file
  warnings.warn(
[I 01:57:43.062 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'load_data' - processing operation dependencies for id: 01ce8ab1-79cf-4e4f-8b18-7e54fdb86487
[I 01:57:43.066 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'load_data' - generated dependency archive: /tmp/elyra/load_data-01ce8ab1-79cf-4e4f-8b18-7e54fdb86487.tar.gz (0.004 secs)
[I 01:57:43.173 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'load_data' - uploaded dependency archive to: hello_world_kubeflow_pipelines-0120015743/load_data-01ce8ab1-79cf-4e4f-8b18-7e54fdb86487.tar.gz (0.044 secs)
[I 01:57:43.174 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'Part 1 - Data Cleaning' - processing operation dependencies for id: 78273cb8-2cba-4d34-b658-fcea96361f82
[I 01:57:43.190 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'Part 1 - Data Cleaning' - generated dependency archive: /tmp/elyra/Part 1 - Data Cleaning-78273cb8-2cba-4d34-b658-fcea96361f82.tar.gz (0.016 secs)
[I 01:57:43.234 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'Part 1 - Data Cleaning' - uploaded dependency archive to: hello_world_kubeflow_pipelines-0120015743/Part 1 - Data Cleaning-78273cb8-2cba-4d34-b658-fcea96361f82.tar.gz (0.039 secs)
[I 01:57:43.234 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743' - pipeline dependencies processed (0.174 secs)
[E 01:57:43.279 LabApp] Uncaught exception POST /notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278 (<IP_ADDRESS>)
    HTTPServerRequest(protocol='http', host='<IP_ADDRESS>:31380', method='POST', uri='/notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278', version='HTTP/1.1', remote_ip='<IP_ADDRESS>')
    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1703, in _execute
        result = await result
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/handlers.py", line 89, in post
        response = await PipelineProcessorManager.instance().process(pipeline)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor.py", line 70, in process
        res = await asyncio.get_event_loop().run_in_executor(None, processor.process, pipeline)
      File "/opt/conda/lib/python3.8/concurrent/futures/thread.py", line 57, in run
        result = self.fn(*self.args, **self.kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor_kfp.py", line 97, in process
        client.upload_pipeline(pipeline_path,
      File "/opt/conda/lib/python3.8/site-packages/kfp/_client.py", line 878, in upload_pipeline
        response = self._upload_api.upload_pipeline(pipeline_package_path, name=pipeline_name, description=description)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 83, in upload_pipeline
        return self.upload_pipeline_with_http_info(uploadfile, **kwargs)  # noqa: E501
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 177, in upload_pipeline_with_http_info
        return self.api_client.call_api(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 378, in call_api
        return self.__call_api(resource_path, method,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 202, in __call_api
        raise e
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 195, in __call_api
        response_data = self.request(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 421, in request
        return self.rest_client.POST(url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 279, in POST
        return self.request("POST", url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 238, in request
        raise ApiException(http_resp=r)
    kfp_server_api.exceptions.ApiException: (404)
    Reason: Not Found
    HTTP response headers: HTTPHeaderDict({'x-powered-by': 'Express', 'content-security-policy': "default-src 'none'", 'x-content-type-options': 'nosniff', 'content-type': 'text/html; charset=utf-8', 'content-length': '180', 'date': 'Wed, 20 Jan 2021 01:57:43 GMT', 'x-envoy-upstream-service-time': '0', 'server': 'istio-envoy'})
    HTTP response body: <!DOCTYPE html>

    <meta charset="utf-8">
    <title>Error</title>

Cannot POST /_/pipeline/apis/v1beta1/pipelines/upload

[E 01:57:43.282 LabApp] Uncaught exception in write_error
    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1703, in _execute
        result = await result
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/handlers.py", line 89, in post
        response = await PipelineProcessorManager.instance().process(pipeline)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor.py", line 70, in process
        res = await asyncio.get_event_loop().run_in_executor(None, processor.process, pipeline)
      File "/opt/conda/lib/python3.8/concurrent/futures/thread.py", line 57, in run
        result = self.fn(*self.args, **self.kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor_kfp.py", line 97, in process
        client.upload_pipeline(pipeline_path,
      File "/opt/conda/lib/python3.8/site-packages/kfp/_client.py", line 878, in upload_pipeline
        response = self._upload_api.upload_pipeline(pipeline_package_path, name=pipeline_name, description=description)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 83, in upload_pipeline
        return self.upload_pipeline_with_http_info(uploadfile, **kwargs)  # noqa: E501
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 177, in upload_pipeline_with_http_info
        return self.api_client.call_api(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 378, in call_api
        return self.__call_api(resource_path, method,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 202, in __call_api
        raise e
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 195, in __call_api
        response_data = self.request(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 421, in request
        return self.rest_client.POST(url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 279, in POST
        return self.request("POST", url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 238, in request
        raise ApiException(http_resp=r)
    kfp_server_api.exceptions.ApiException: (404)
    Reason: Not Found
    HTTP response headers: HTTPHeaderDict({'x-powered-by': 'Express', 'content-security-policy': "default-src 'none'", 'x-content-type-options': 'nosniff', 'content-type': 'text/html; charset=utf-8', 'content-length': '180', 'date': 'Wed, 20 Jan 2021 01:57:43 GMT', 'x-envoy-upstream-service-time': '0', 'server': 'istio-envoy'})
    HTTP response body: <!DOCTYPE html>

    <meta charset="utf-8">
    <title>Error</title>

Cannot POST /_/pipeline/apis/v1beta1/pipelines/upload

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1218, in send_error
        self.write_error(status_code, **kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/util/http.py", line 64, in write_error
        reply['message'] = exception.args[0]
    IndexError: tuple index out of range
[E 01:57:43.284 LabApp] {
      "Host": "<IP_ADDRESS>:31380",
      "Content-Length": "2983",
      "Origin": "http://<IP_ADDRESS>:31380",
      "X-Xsrftoken": "2|735c12db|1e17c73f8623a002c1b780700338be7a|1610505787",
      "User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36",
      "Content-Type": "application/json",
      "Accept": "*/*",
      "Referer": "http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?",
      "Accept-Encoding": "gzip, deflate",
      "Accept-Language": "zh-CN,zh;q=0.9",
      "Cookie": "_ga=GA1.1.1786415111.1600928397; sidebar_collapsed=false; login_region=\"http://controller:5000/v3\"; login_domain=demo; _xsrf=2|735c12db|1e17c73f8623a002c1b780700338be7a|1610505787",
      "X-Forwarded-For": "<IP_ADDRESS>",
      "X-Forwarded-Proto": "http",
      "X-Request-Id": "b41daaef-108b-92a4-bef9-661891e9770d",
      "Kubeflow-Userid"<EMAIL_ADDRESS>      "X-Envoy-Expected-Rq-Timeout-Ms": "300000",
      "X-Envoy-Original-Path": "/notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278",
      "X-Envoy-Internal": "true",
      "X-B3-Traceid": "a660c8d7e0cb9bc9a2af6dd2c634eed5",
      "X-B3-Spanid": "52c7fa1f23657fc3",
      "X-B3-Parentspanid": "a2af6dd2c634eed5",
      "X-B3-Sampled": "1"
    }
[E 01:57:43.284 LabApp] 500 POST /notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278 (<IP_ADDRESS>) 241.63ms referer=http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?

thank you

Ah yes, so you've created a Notebook Server as described in https://v1-0-branch.kubeflow.org/docs/notebooks/setup/ and specified a custom container image? If that's the case, can you please share the image's Dockerfile?
I know @lresende has been looking into this type of deployment in the past.
I don't have access to such a configuration but it is my understanding that you should be able to access the JupyterLab log file using kubectl logs -n kubeflow pod/XXX replacing XXX with the server's pod name.

hi @ptitzler
i can share my dockerfile:
FROM debian:latest

ENV LANG=C.UTF-8 LC_ALL=C.UTF-8
ENV PATH /opt/conda/bin:$PATH
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update --fix-missing && apt-get install -y wget bzip2 ca-certificates \
    libglib2.0-0 libxext6 libsm6 libxrender1 \
    git mercurial subversion

RUN wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2020.07-Linux-x86_64.sh  -O ~/anaconda.sh && \
    /bin/bash ~/anaconda.sh -b -p /opt/conda && \
    rm ~/anaconda.sh && \
    ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh && \
    echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc && \
    echo "conda activate base" >> ~/.bashrc

RUN apt-get install -y curl grep sed dpkg && \
    TINI_VERSION=`curl https://github.com/krallin/tini/releases/latest | grep -o "/v.*\"" | sed 's:^..\(.*\).$:\1:'` && \
    curl -L "https://github.com/krallin/tini/releases/download/v${TINI_VERSION}/tini_${TINI_VERSION}.deb" > tini.deb && \
    dpkg -i tini.deb && \
    rm tini.deb && \
    apt-get clean

RUN conda install tensorflow \
    && conda install keras -y \
    && pip install cryptography -i https://pypi.tuna.tsinghua.edu.cn/simple \
    && pip install pandas -i https://pypi.tuna.tsinghua.edu.cn/simple \
    && pip install seaborn -i https://pypi.tuna.tsinghua.edu.cn/simple \
    && pip install scikit-learn -i https://pypi.tuna.tsinghua.edu.cn/simple \
    && pip install matplotlib -i https://pypi.tuna.tsinghua.edu.cn/simple \
    && pip install jieba -i https://pypi.tuna.tsinghua.edu.cn/simple

RUN conda install -c conda-forge/label/cf202003 nodejs
RUN pip install --upgrade "elyra<2.0.0" && jupyter lab build

WORKDIR /home/jovyan

USER root

ARG NB_USER=jovyan

EXPOSE 8888

ENV NB_USER $NB_USER
ENV NB_UID=1000
ENV HOME /home/$NB_USER

ENV NB_PREFIX /

CMD ["sh","-c", "jupyter lab --notebook-dir=/home/jovyan --ip=<IP_ADDRESS> --no-browser --allow-root --port=8888 --NotebookApp.token='' --NotebookApp.password='' --NotebookApp.allow_origin='*' --NotebookApp.base_url=${NB_PREFIX}"]

and the following is the logs in pod:
[I 01:57:37.169 LabApp] Saving file at /hello_world_kubeflow_pipelines.pipeline
[W 01:57:37.871 LabApp] Notebook load_data.ipynb is not trusted
[W 01:57:37.952 LabApp] Notebook Part 1 - Data Cleaning.ipynb is not trusted
[I 01:57:43.048 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743' - submitting pipeline
[I 01:57:43.060 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743' - processing pipeline dependencies to: http://<IP_ADDRESS>:9000/ bucket: test folder: hello_world_kubeflow_pipelines-0120015743
/opt/conda/lib/python3.8/site-packages/kfp/dsl/_container_op.py:1021: FutureWarning: Please create reusable components instead of constructing ContainerOp instances directly. Reusable components are shareable, portable and have compatibility and support guarantees. Please see the documentation: https://www.kubeflow.org/docs/pipelines/sdk/component-development/#writing-your-component-definition-file The components can be created manually (or, in case of python, using kfp.components.create_component_from_func or func_to_container_op) and then loaded using kfp.components.load_component_from_file, load_component_from_uri or load_component_from_text: https://kubeflow-pipelines.readthedocs.io/en/stable/source/kfp.components.html#kfp.components.load_component_from_file
  warnings.warn(
[I 01:57:43.062 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'load_data' - processing operation dependencies for id: 01ce8ab1-79cf-4e4f-8b18-7e54fdb86487
[I 01:57:43.066 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'load_data' - generated dependency archive: /tmp/elyra/load_data-01ce8ab1-79cf-4e4f-8b18-7e54fdb86487.tar.gz (0.004 secs)
[I 01:57:43.173 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'load_data' - uploaded dependency archive to: hello_world_kubeflow_pipelines-0120015743/load_data-01ce8ab1-79cf-4e4f-8b18-7e54fdb86487.tar.gz (0.044 secs)
[I 01:57:43.174 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'Part 1 - Data Cleaning' - processing operation dependencies for id: 78273cb8-2cba-4d34-b658-fcea96361f82
[I 01:57:43.190 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'Part 1 - Data Cleaning' - generated dependency archive: /tmp/elyra/Part 1 - Data Cleaning-78273cb8-2cba-4d34-b658-fcea96361f82.tar.gz (0.016 secs)
[I 01:57:43.234 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743':'Part 1 - Data Cleaning' - uploaded dependency archive to: hello_world_kubeflow_pipelines-0120015743/Part 1 - Data Cleaning-78273cb8-2cba-4d34-b658-fcea96361f82.tar.gz (0.039 secs)
[I 01:57:43.234 LabApp] kfp 'hello_world_kubeflow_pipelines-0120015743' - pipeline dependencies processed (0.174 secs)
[E 01:57:43.279 LabApp] Uncaught exception POST /notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278 (<IP_ADDRESS>)
    HTTPServerRequest(protocol='http', host='<IP_ADDRESS>:31380', method='POST', uri='/notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278', version='HTTP/1.1', remote_ip='<IP_ADDRESS>')
    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1703, in _execute
        result = await result
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/handlers.py", line 89, in post
        response = await PipelineProcessorManager.instance().process(pipeline)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor.py", line 70, in process
        res = await asyncio.get_event_loop().run_in_executor(None, processor.process, pipeline)
      File "/opt/conda/lib/python3.8/concurrent/futures/thread.py", line 57, in run
        result = self.fn(*self.args, **self.kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor_kfp.py", line 97, in process
        client.upload_pipeline(pipeline_path,
      File "/opt/conda/lib/python3.8/site-packages/kfp/_client.py", line 878, in upload_pipeline
        response = self._upload_api.upload_pipeline(pipeline_package_path, name=pipeline_name, description=description)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 83, in upload_pipeline
        return self.upload_pipeline_with_http_info(uploadfile, **kwargs)  # noqa: E501
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 177, in upload_pipeline_with_http_info
        return self.api_client.call_api(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 378, in call_api
        return self.__call_api(resource_path, method,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 202, in __call_api
        raise e
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 195, in __call_api
        response_data = self.request(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 421, in request
        return self.rest_client.POST(url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 279, in POST
        return self.request("POST", url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 238, in request
        raise ApiException(http_resp=r)
    kfp_server_api.exceptions.ApiException: (404)
    Reason: Not Found
    HTTP response headers: HTTPHeaderDict({'x-powered-by': 'Express', 'content-security-policy': "default-src 'none'", 'x-content-type-options': 'nosniff', 'content-type': 'text/html; charset=utf-8', 'content-length': '180', 'date': 'Wed, 20 Jan 2021 01:57:43 GMT', 'x-envoy-upstream-service-time': '0', 'server': 'istio-envoy'})
    HTTP response body: <!DOCTYPE html>

    <meta charset="utf-8">
    <title>Error</title>

Cannot POST /_/pipeline/apis/v1beta1/pipelines/upload

[E 01:57:43.282 LabApp] Uncaught exception in write_error
    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1703, in _execute
        result = await result
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/handlers.py", line 89, in post
        response = await PipelineProcessorManager.instance().process(pipeline)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor.py", line 70, in process
        res = await asyncio.get_event_loop().run_in_executor(None, processor.process, pipeline)
      File "/opt/conda/lib/python3.8/concurrent/futures/thread.py", line 57, in run
        result = self.fn(*self.args, **self.kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor_kfp.py", line 97, in process
        client.upload_pipeline(pipeline_path,
      File "/opt/conda/lib/python3.8/site-packages/kfp/_client.py", line 878, in upload_pipeline
        response = self._upload_api.upload_pipeline(pipeline_package_path, name=pipeline_name, description=description)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 83, in upload_pipeline
        return self.upload_pipeline_with_http_info(uploadfile, **kwargs)  # noqa: E501
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 177, in upload_pipeline_with_http_info
        return self.api_client.call_api(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 378, in call_api
        return self.__call_api(resource_path, method,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 202, in __call_api
        raise e
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 195, in __call_api
        response_data = self.request(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 421, in request
        return self.rest_client.POST(url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 279, in POST
        return self.request("POST", url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 238, in request
        raise ApiException(http_resp=r)
    kfp_server_api.exceptions.ApiException: (404)
    Reason: Not Found
    HTTP response headers: HTTPHeaderDict({'x-powered-by': 'Express', 'content-security-policy': "default-src 'none'", 'x-content-type-options': 'nosniff', 'content-type': 'text/html; charset=utf-8', 'content-length': '180', 'date': 'Wed, 20 Jan 2021 01:57:43 GMT', 'x-envoy-upstream-service-time': '0', 'server': 'istio-envoy'})
    HTTP response body: <!DOCTYPE html>

    <meta charset="utf-8">
    <title>Error</title>

Cannot POST /_/pipeline/apis/v1beta1/pipelines/upload

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1218, in send_error
        self.write_error(status_code, **kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/util/http.py", line 64, in write_error
        reply['message'] = exception.args[0]
    IndexError: tuple index out of range
[E 01:57:43.284 LabApp] {
      "Host": "<IP_ADDRESS>:31380",
      "Content-Length": "2983",
      "Origin": "http://<IP_ADDRESS>:31380",
      "X-Xsrftoken": "2|735c12db|1e17c73f8623a002c1b780700338be7a|1610505787",
      "User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36",
      "Content-Type": "application/json",
      "Accept": "*/*",
      "Referer": "http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?",
      "Accept-Encoding": "gzip, deflate",
      "Accept-Language": "zh-CN,zh;q=0.9",
      "Cookie": "_ga=GA1.1.1786415111.1600928397; sidebar_collapsed=false; login_region=\"http://controller:5000/v3\"; login_domain=demo; _xsrf=2|735c12db|1e17c73f8623a002c1b780700338be7a|1610505787",
      "X-Forwarded-For": "<IP_ADDRESS>",
      "X-Forwarded-Proto": "http",
      "X-Request-Id": "b41daaef-108b-92a4-bef9-661891e9770d",
      "Kubeflow-Userid"<EMAIL_ADDRESS>      "X-Envoy-Expected-Rq-Timeout-Ms": "300000",
      "X-Envoy-Original-Path": "/notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278",
      "X-Envoy-Internal": "true",
      "X-B3-Traceid": "a660c8d7e0cb9bc9a2af6dd2c634eed5",
      "X-B3-Spanid": "52c7fa1f23657fc3",
      "X-B3-Parentspanid": "a2af6dd2c634eed5",
      "X-B3-Sampled": "1"
    }
[E 01:57:43.284 LabApp] 500 POST /notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278 (<IP_ADDRESS>) 241.63ms referer=http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?

thank you

Ah yes. It appears that your configured endpoint URL is likely invalid.

Could you please change the Pipelines API endpoint to http://<IP_ADDRESS>:31380/pipeline in your runtime configuration and try again?

Ah yes. It appears that your configured endpoint URL is likely invalid.

Could you please change the Pipelines API endpoint to http://<IP_ADDRESS>:31380/pipeline in your runtime configuration and try again?

Ah yes. It appears that your configured endpoint URL is likely invalid.

Could you please change the Pipelines API endpoint to http://<IP_ADDRESS>:31380/pipeline in your runtime configuration and try again?

hi @ptitzler
i changed the pipeline API endpoint, it shows the following error:

[E 01:57:43.282 LabApp] Uncaught exception in write_error
    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1703, in _execute
        result = await result
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/handlers.py", line 89, in post
        response = await PipelineProcessorManager.instance().process(pipeline)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor.py", line 70, in process
        res = await asyncio.get_event_loop().run_in_executor(None, processor.process, pipeline)
      File "/opt/conda/lib/python3.8/concurrent/futures/thread.py", line 57, in run
        result = self.fn(*self.args, **self.kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor_kfp.py", line 97, in process
        client.upload_pipeline(pipeline_path,
      File "/opt/conda/lib/python3.8/site-packages/kfp/_client.py", line 878, in upload_pipeline
        response = self._upload_api.upload_pipeline(pipeline_package_path, name=pipeline_name, description=description)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 83, in upload_pipeline
        return self.upload_pipeline_with_http_info(uploadfile, **kwargs)  # noqa: E501
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 177, in upload_pipeline_with_http_info
        return self.api_client.call_api(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 378, in call_api
        return self.__call_api(resource_path, method,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 202, in __call_api
        raise e
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 195, in __call_api
        response_data = self.request(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 421, in request
        return self.rest_client.POST(url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 279, in POST
        return self.request("POST", url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 238, in request
        raise ApiException(http_resp=r)
    kfp_server_api.exceptions.ApiException: (404)
    Reason: Not Found
    HTTP response headers: HTTPHeaderDict({'x-powered-by': 'Express', 'content-security-policy': "default-src 'none'", 'x-content-type-options': 'nosniff', 'content-type': 'text/html; charset=utf-8', 'content-length': '180', 'date': 'Wed, 20 Jan 2021 01:57:43 GMT', 'x-envoy-upstream-service-time': '0', 'server': 'istio-envoy'})
    HTTP response body: <!DOCTYPE html>

    <meta charset="utf-8">
    <title>Error</title>

Cannot POST /_/pipeline/apis/v1beta1/pipelines/upload

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1218, in send_error
        self.write_error(status_code, **kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/util/http.py", line 64, in write_error
        reply['message'] = exception.args[0]
    IndexError: tuple index out of range
[E 01:57:43.284 LabApp] {
      "Host": "<IP_ADDRESS>:31380",
      "Content-Length": "2983",
      "Origin": "http://<IP_ADDRESS>:31380",
      "X-Xsrftoken": "2|735c12db|1e17c73f8623a002c1b780700338be7a|1610505787",
      "User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36",
      "Content-Type": "application/json",
      "Accept": "*/*",
      "Referer": "http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?",
      "Accept-Encoding": "gzip, deflate",
      "Accept-Language": "zh-CN,zh;q=0.9",
      "Cookie": "_ga=GA1.1.1786415111.1600928397; sidebar_collapsed=false; login_region=\"http://controller:5000/v3\"; login_domain=demo; _xsrf=2|735c12db|1e17c73f8623a002c1b780700338be7a|1610505787",
      "X-Forwarded-For": "<IP_ADDRESS>",
      "X-Forwarded-Proto": "http",
      "X-Request-Id": "b41daaef-108b-92a4-bef9-661891e9770d",
      "Kubeflow-Userid"<EMAIL_ADDRESS>      "X-Envoy-Expected-Rq-Timeout-Ms": "300000",
      "X-Envoy-Original-Path": "/notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278",
      "X-Envoy-Internal": "true",
      "X-B3-Traceid": "a660c8d7e0cb9bc9a2af6dd2c634eed5",
      "X-B3-Spanid": "52c7fa1f23657fc3",
      "X-B3-Parentspanid": "a2af6dd2c634eed5",
      "X-B3-Sampled": "1"
    }
[E 01:57:43.284 LabApp] 500 POST /notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278 (<IP_ADDRESS>) 241.63ms referer=http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?

could you teach me how to solve this error.
thank you

Ah yes. It appears that your configured endpoint URL is likely invalid.

Could you please change the Pipelines API endpoint to http://<IP_ADDRESS>:31380/pipeline in your runtime configuration and try again?

hi @ptitzler
i changed the pipeline API endpoint, it shows the following error:

[E 01:57:43.282 LabApp] Uncaught exception in write_error
    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1703, in _execute
        result = await result
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/handlers.py", line 89, in post
        response = await PipelineProcessorManager.instance().process(pipeline)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor.py", line 70, in process
        res = await asyncio.get_event_loop().run_in_executor(None, processor.process, pipeline)
      File "/opt/conda/lib/python3.8/concurrent/futures/thread.py", line 57, in run
        result = self.fn(*self.args, **self.kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor_kfp.py", line 97, in process
        client.upload_pipeline(pipeline_path,
      File "/opt/conda/lib/python3.8/site-packages/kfp/_client.py", line 878, in upload_pipeline
        response = self._upload_api.upload_pipeline(pipeline_package_path, name=pipeline_name, description=description)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 83, in upload_pipeline
        return self.upload_pipeline_with_http_info(uploadfile, **kwargs)  # noqa: E501
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 177, in upload_pipeline_with_http_info
        return self.api_client.call_api(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 378, in call_api
        return self.__call_api(resource_path, method,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 202, in __call_api
        raise e
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 195, in __call_api
        response_data = self.request(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 421, in request
        return self.rest_client.POST(url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 279, in POST
        return self.request("POST", url,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/rest.py", line 238, in request
        raise ApiException(http_resp=r)
    kfp_server_api.exceptions.ApiException: (404)
    Reason: Not Found
    HTTP response headers: HTTPHeaderDict({'x-powered-by': 'Express', 'content-security-policy': "default-src 'none'", 'x-content-type-options': 'nosniff', 'content-type': 'text/html; charset=utf-8', 'content-length': '180', 'date': 'Wed, 20 Jan 2021 01:57:43 GMT', 'x-envoy-upstream-service-time': '0', 'server': 'istio-envoy'})
    HTTP response body: <!DOCTYPE html>

    <meta charset="utf-8">
    <title>Error</title>

Cannot POST /_/pipeline/apis/v1beta1/pipelines/upload

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1218, in send_error
        self.write_error(status_code, **kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/util/http.py", line 64, in write_error
        reply['message'] = exception.args[0]
    IndexError: tuple index out of range
[E 01:57:43.284 LabApp] {
      "Host": "<IP_ADDRESS>:31380",
      "Content-Length": "2983",
      "Origin": "http://<IP_ADDRESS>:31380",
      "X-Xsrftoken": "2|735c12db|1e17c73f8623a002c1b780700338be7a|1610505787",
      "User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36",
      "Content-Type": "application/json",
      "Accept": "*/*",
      "Referer": "http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?",
      "Accept-Encoding": "gzip, deflate",
      "Accept-Language": "zh-CN,zh;q=0.9",
      "Cookie": "_ga=GA1.1.1786415111.1600928397; sidebar_collapsed=false; login_region=\"http://controller:5000/v3\"; login_domain=demo; _xsrf=2|735c12db|1e17c73f8623a002c1b780700338be7a|1610505787",
      "X-Forwarded-For": "<IP_ADDRESS>",
      "X-Forwarded-Proto": "http",
      "X-Request-Id": "b41daaef-108b-92a4-bef9-661891e9770d",
      "Kubeflow-Userid"<EMAIL_ADDRESS>      "X-Envoy-Expected-Rq-Timeout-Ms": "300000",
      "X-Envoy-Original-Path": "/notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278",
      "X-Envoy-Internal": "true",
      "X-B3-Traceid": "a660c8d7e0cb9bc9a2af6dd2c634eed5",
      "X-B3-Spanid": "52c7fa1f23657fc3",
      "X-B3-Parentspanid": "a2af6dd2c634eed5",
      "X-B3-Sampled": "1"
    }
[E 01:57:43.284 LabApp] 500 POST /notebook/gjzx/tony/elyra/pipeline/schedule?1611107876278 (<IP_ADDRESS>) 241.63ms referer=http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?

could you teach me how to solve this error.
thank you

Could you please attach the log file for this new error symptom? The error dialog screen capture doesn't have enough details to identify where the problem is occurring.

Could you please attach the log file for this new error symptom? The error dialog screen capture doesn't have enough details to identify where the problem is occurring.

Could you please attach the log file for this new error symptom? The error dialog screen capture doesn't have enough details to identify where the problem is occurring.

hi @ptitzler
this is the whole log file after i run the Elyra by pipeline:
[W 07:29:13.652 LabApp] Notebook load_data.ipynb is not trusted
[W 07:29:13.745 LabApp] Notebook Part 1 - Data Cleaning.ipynb is not trusted
[I 07:29:15.415 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915' - submitting pipeline
[I 07:29:15.419 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915' - processing pipeline dependencies to: http://<IP_ADDRESS>:9000/ bucket: test folder: hello_world_kubeflow_pipelines-0122072915
/opt/conda/lib/python3.8/site-packages/kfp/dsl/_container_op.py:1021: FutureWarning: Please create reusable components instead of constructing ContainerOp instances directly. Reusable components are shareable, portable and have compatibility and support guarantees. Please see the documentation: https://www.kubeflow.org/docs/pipelines/sdk/component-development/#writing-your-component-definition-file The components can be created manually (or, in case of python, using kfp.components.create_component_from_func or func_to_container_op) and then loaded using kfp.components.load_component_from_file, load_component_from_uri or load_component_from_text: https://kubeflow-pipelines.readthedocs.io/en/stable/source/kfp.components.html#kfp.components.load_component_from_file
  warnings.warn(
[I 07:29:15.421 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'load_data' - processing operation dependencies for id: 01ce8ab1-79cf-4e4f-8b18-7e54fdb86487
[I 07:29:15.424 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'load_data' - generated dependency archive: /tmp/elyra/load_data-01ce8ab1-79cf-4e4f-8b18-7e54fdb86487.tar.gz (0.003 secs)
[I 07:29:15.638 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'load_data' - uploaded dependency archive to: hello_world_kubeflow_pipelines-0122072915/load_data-01ce8ab1-79cf-4e4f-8b18-7e54fdb86487.tar.gz (0.023 secs)
[I 07:29:15.638 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'Part 1 - Data Cleaning' - processing operation dependencies for id: 78273cb8-2cba-4d34-b658-fcea96361f82
[I 07:29:15.655 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'Part 1 - Data Cleaning' - generated dependency archive: /tmp/elyra/Part 1 - Data Cleaning-78273cb8-2cba-4d34-b658-fcea96361f82.tar.gz (0.016 secs)
[I 07:29:15.705 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'Part 1 - Data Cleaning' - uploaded dependency archive to: hello_world_kubeflow_pipelines-0122072915/Part 1 - Data Cleaning-78273cb8-2cba-4d34-b658-fcea96361f82.tar.gz (0.045 secs)
[I 07:29:15.705 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915' - pipeline dependencies processed (0.286 secs)
[E 07:29:15.913 LabApp] Uncaught exception POST /notebook/gjzx/tony/elyra/pipeline/schedule?1611300619295 (<IP_ADDRESS>)
    HTTPServerRequest(protocol='http', host='<IP_ADDRESS>:31380', method='POST', uri='/notebook/gjzx/tony/elyra/pipeline/schedule?1611300619295', version='HTTP/1.1', remote_ip='<IP_ADDRESS>')
    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1703, in _execute
        result = await result
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/handlers.py", line 89, in post
        response = await PipelineProcessorManager.instance().process(pipeline)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor.py", line 70, in process
        res = await asyncio.get_event_loop().run_in_executor(None, processor.process, pipeline)
      File "/opt/conda/lib/python3.8/concurrent/futures/thread.py", line 57, in run
        result = self.fn(*self.args, **self.kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor_kfp.py", line 97, in process
        client.upload_pipeline(pipeline_path,
      File "/opt/conda/lib/python3.8/site-packages/kfp/_client.py", line 878, in upload_pipeline
        response = self._upload_api.upload_pipeline(pipeline_package_path, name=pipeline_name, description=description)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 83, in upload_pipeline
        return self.upload_pipeline_with_http_info(uploadfile, **kwargs)  # noqa: E501
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 177, in upload_pipeline_with_http_info
        return self.api_client.call_api(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 378, in call_api
        return self.__call_api(resource_path, method,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 222, in __call_api
        return_data = self.deserialize(response_data, response_type)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 294, in deserialize
        return self.__deserialize(data, response_type)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 333, in __deserialize
        return self.__deserialize_model(data, klass)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 672, in __deserialize_model
        kwargs[attr] = self.__deserialize(value, attr_type)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 333, in __deserialize
        return self.__deserialize_model(data, klass)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 672, in __deserialize_model
        kwargs[attr] = self.__deserialize(value, attr_type)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 331, in __deserialize
        return self.__deserialize_datetime(data)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 638, in __deserialize_datetime
        return parse(string)
      File "/opt/conda/lib/python3.8/site-packages/dateutil/parser/_parser.py", line 1374, in parse
        return DEFAULTPARSER.parse(timestr, **kwargs)
      File "/opt/conda/lib/python3.8/site-packages/dateutil/parser/_parser.py", line 646, in parse
        res, skipped_tokens = self._parse(timestr, **kwargs)
      File "/opt/conda/lib/python3.8/site-packages/dateutil/parser/_parser.py", line 725, in _parse
        l = _timelex.split(timestr)         # Splits the timestr into tokens
      File "/opt/conda/lib/python3.8/site-packages/dateutil/parser/_parser.py", line 207, in split
        return list(cls(s))
      File "/opt/conda/lib/python3.8/site-packages/dateutil/parser/_parser.py", line 75, in __init__
        raise TypeError('Parser must be a string or character stream, not '
    TypeError: Parser must be a string or character stream, not dict
[E 07:29:15.915 LabApp] {
      "Host": "<IP_ADDRESS>:31380",
      "Content-Length": "2984",
      "X-Xsrftoken": "2|73f825ae|85bfc7359df22f96033a3b262837a0d0|1610343339",
      "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36",
      "Content-Type": "application/json",
      "Accept": "*/*",
      "Origin": "http://<IP_ADDRESS>:31380",
      "Referer": "http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?",
      "Accept-Encoding": "gzip, deflate",
      "Accept-Language": "zh-CN,zh;q=0.9",
      "Cookie": "_xsrf=2|73f825ae|85bfc7359df22f96033a3b262837a0d0|1610343339",
      "X-Forwarded-For": "<IP_ADDRESS>",
      "X-Forwarded-Proto": "http",
      "X-Request-Id": "285ef49a-7d4a-903d-a3cf-f16e0ac4b583",
      "Kubeflow-Userid"<EMAIL_ADDRESS>      "X-Envoy-Expected-Rq-Timeout-Ms": "300000",
      "X-Envoy-Original-Path": "/notebook/gjzx/tony/elyra/pipeline/schedule?1611300619295",
      "X-Envoy-Internal": "true",
      "X-B3-Traceid": "4a98678562d0fbfbaef73326ab9a7b0d",
      "X-B3-Spanid": "4a99a2c94e9ebea4",
      "X-B3-Parentspanid": "aef73326ab9a7b0d",
      "X-B3-Sampled": "1"
    }
[E 07:29:15.915 LabApp] 500 POST /notebook/gjzx/tony/elyra/pipeline/schedule?1611300619295 (<IP_ADDRESS>) 505.70ms referer=http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?

Could you please attach the log file for this new error symptom? The error dialog screen capture doesn't have enough details to identify where the problem is occurring.

hi @ptitzler
this is the whole log file after i run the Elyra by pipeline:
[W 07:29:13.652 LabApp] Notebook load_data.ipynb is not trusted
[W 07:29:13.745 LabApp] Notebook Part 1 - Data Cleaning.ipynb is not trusted
[I 07:29:15.415 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915' - submitting pipeline
[I 07:29:15.419 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915' - processing pipeline dependencies to: http://<IP_ADDRESS>:9000/ bucket: test folder: hello_world_kubeflow_pipelines-0122072915
/opt/conda/lib/python3.8/site-packages/kfp/dsl/_container_op.py:1021: FutureWarning: Please create reusable components instead of constructing ContainerOp instances directly. Reusable components are shareable, portable and have compatibility and support guarantees. Please see the documentation: https://www.kubeflow.org/docs/pipelines/sdk/component-development/#writing-your-component-definition-file The components can be created manually (or, in case of python, using kfp.components.create_component_from_func or func_to_container_op) and then loaded using kfp.components.load_component_from_file, load_component_from_uri or load_component_from_text: https://kubeflow-pipelines.readthedocs.io/en/stable/source/kfp.components.html#kfp.components.load_component_from_file
  warnings.warn(
[I 07:29:15.421 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'load_data' - processing operation dependencies for id: 01ce8ab1-79cf-4e4f-8b18-7e54fdb86487
[I 07:29:15.424 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'load_data' - generated dependency archive: /tmp/elyra/load_data-01ce8ab1-79cf-4e4f-8b18-7e54fdb86487.tar.gz (0.003 secs)
[I 07:29:15.638 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'load_data' - uploaded dependency archive to: hello_world_kubeflow_pipelines-0122072915/load_data-01ce8ab1-79cf-4e4f-8b18-7e54fdb86487.tar.gz (0.023 secs)
[I 07:29:15.638 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'Part 1 - Data Cleaning' - processing operation dependencies for id: 78273cb8-2cba-4d34-b658-fcea96361f82
[I 07:29:15.655 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'Part 1 - Data Cleaning' - generated dependency archive: /tmp/elyra/Part 1 - Data Cleaning-78273cb8-2cba-4d34-b658-fcea96361f82.tar.gz (0.016 secs)
[I 07:29:15.705 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915':'Part 1 - Data Cleaning' - uploaded dependency archive to: hello_world_kubeflow_pipelines-0122072915/Part 1 - Data Cleaning-78273cb8-2cba-4d34-b658-fcea96361f82.tar.gz (0.045 secs)
[I 07:29:15.705 LabApp] kfp 'hello_world_kubeflow_pipelines-0122072915' - pipeline dependencies processed (0.286 secs)
[E 07:29:15.913 LabApp] Uncaught exception POST /notebook/gjzx/tony/elyra/pipeline/schedule?1611300619295 (<IP_ADDRESS>)
    HTTPServerRequest(protocol='http', host='<IP_ADDRESS>:31380', method='POST', uri='/notebook/gjzx/tony/elyra/pipeline/schedule?1611300619295', version='HTTP/1.1', remote_ip='<IP_ADDRESS>')
    Traceback (most recent call last):
      File "/opt/conda/lib/python3.8/site-packages/tornado/web.py", line 1703, in _execute
        result = await result
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/handlers.py", line 89, in post
        response = await PipelineProcessorManager.instance().process(pipeline)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor.py", line 70, in process
        res = await asyncio.get_event_loop().run_in_executor(None, processor.process, pipeline)
      File "/opt/conda/lib/python3.8/concurrent/futures/thread.py", line 57, in run
        result = self.fn(*self.args, **self.kwargs)
      File "/opt/conda/lib/python3.8/site-packages/elyra/pipeline/processor_kfp.py", line 97, in process
        client.upload_pipeline(pipeline_path,
      File "/opt/conda/lib/python3.8/site-packages/kfp/_client.py", line 878, in upload_pipeline
        response = self._upload_api.upload_pipeline(pipeline_package_path, name=pipeline_name, description=description)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 83, in upload_pipeline
        return self.upload_pipeline_with_http_info(uploadfile, **kwargs)  # noqa: E501
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 177, in upload_pipeline_with_http_info
        return self.api_client.call_api(
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 378, in call_api
        return self.__call_api(resource_path, method,
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 222, in __call_api
        return_data = self.deserialize(response_data, response_type)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 294, in deserialize
        return self.__deserialize(data, response_type)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 333, in __deserialize
        return self.__deserialize_model(data, klass)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 672, in __deserialize_model
        kwargs[attr] = self.__deserialize(value, attr_type)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 333, in __deserialize
        return self.__deserialize_model(data, klass)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 672, in __deserialize_model
        kwargs[attr] = self.__deserialize(value, attr_type)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 331, in __deserialize
        return self.__deserialize_datetime(data)
      File "/opt/conda/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 638, in __deserialize_datetime
        return parse(string)
      File "/opt/conda/lib/python3.8/site-packages/dateutil/parser/_parser.py", line 1374, in parse
        return DEFAULTPARSER.parse(timestr, **kwargs)
      File "/opt/conda/lib/python3.8/site-packages/dateutil/parser/_parser.py", line 646, in parse
        res, skipped_tokens = self._parse(timestr, **kwargs)
      File "/opt/conda/lib/python3.8/site-packages/dateutil/parser/_parser.py", line 725, in _parse
        l = _timelex.split(timestr)         # Splits the timestr into tokens
      File "/opt/conda/lib/python3.8/site-packages/dateutil/parser/_parser.py", line 207, in split
        return list(cls(s))
      File "/opt/conda/lib/python3.8/site-packages/dateutil/parser/_parser.py", line 75, in __init__
        raise TypeError('Parser must be a string or character stream, not '
    TypeError: Parser must be a string or character stream, not dict
[E 07:29:15.915 LabApp] {
      "Host": "<IP_ADDRESS>:31380",
      "Content-Length": "2984",
      "X-Xsrftoken": "2|73f825ae|85bfc7359df22f96033a3b262837a0d0|1610343339",
      "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36",
      "Content-Type": "application/json",
      "Accept": "*/*",
      "Origin": "http://<IP_ADDRESS>:31380",
      "Referer": "http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?",
      "Accept-Encoding": "gzip, deflate",
      "Accept-Language": "zh-CN,zh;q=0.9",
      "Cookie": "_xsrf=2|73f825ae|85bfc7359df22f96033a3b262837a0d0|1610343339",
      "X-Forwarded-For": "<IP_ADDRESS>",
      "X-Forwarded-Proto": "http",
      "X-Request-Id": "285ef49a-7d4a-903d-a3cf-f16e0ac4b583",
      "Kubeflow-Userid"<EMAIL_ADDRESS>      "X-Envoy-Expected-Rq-Timeout-Ms": "300000",
      "X-Envoy-Original-Path": "/notebook/gjzx/tony/elyra/pipeline/schedule?1611300619295",
      "X-Envoy-Internal": "true",
      "X-B3-Traceid": "4a98678562d0fbfbaef73326ab9a7b0d",
      "X-B3-Spanid": "4a99a2c94e9ebea4",
      "X-B3-Parentspanid": "aef73326ab9a7b0d",
      "X-B3-Sampled": "1"
    }
[E 07:29:15.915 LabApp] 500 POST /notebook/gjzx/tony/elyra/pipeline/schedule?1611300619295 (<IP_ADDRESS>) 505.70ms referer=http://<IP_ADDRESS>:31380/notebook/gjzx/tony/lab?

I am also having the same issue. I have the same pipeline structure. Minio works fine but there is a problem with the kubeflow. Here you can find my logs:
`
Uncaught exception in write_error
Traceback (most recent call last):
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/tornado/web.py", line 1704, in _execute
result = await result
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/elyra/pipeline/handlers.py", line 89, in post
response = await PipelineProcessorManager.instance().process(pipeline)
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/elyra/pipeline/processor.py", line 70, in process
res = await asyncio.get_event_loop().run_in_executor(None, processor.process, pipeline)
File "/Users/anaconda3/envs/smartix/lib/python3.8/concurrent/futures/thread.py", line 57, in run
result = self.fn(*self.args, **self.kwargs)
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/elyra/pipeline/processor_kfp.py", line 97, in process
client.upload_pipeline(pipeline_path,
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp/_client.py", line 878, in upload_pipeline
response = self.upload_api.upload_pipeline(pipeline_package_path, name=pipeline_name, description=description)
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 83, in upload_pipeline
return self.upload_pipeline_with_http_info(uploadfile, **kwargs)  # noqa: E501
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 177, in upload_pipeline_with_http_info
return self.api_client.call_api(
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 378, in call_api
return self.__call_api(resource_path, method,
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 202, in __call_api
raise e
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 195, in __call_api
response_data = self.request(
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 421, in request
return self.rest_client.POST(url,
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/rest.py", line 279, in POST
return self.request("POST", url,
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/rest.py", line 238, in request
raise ApiException(http_resp=r)
kfp_server_api.exceptions.ApiException: (404)
Reason: Not Found
HTTP response headers: HTTPHeaderDict({'x-powered-by': 'Express', 'content-security-policy': "default-src 'none'", 'x-content-type-options': 'nosniff', 'content-type': 'text/html; charset=utf-8', 'content-length': '180', 'date': 'Fri, 22 Jan 2021 15:40:02 GMT', 'x-envoy-upstream-service-time': '1', 'server': 'istio-envoy'})
HTTP response body:

Error

Cannot POST //pipeline/apis/v1beta1/pipelines/upload

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/tornado/web.py", line 1217, in send_error
    self.write_error(status_code, **kwargs)
  File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/elyra/util/http.py", line 64, in write_error
    reply['message'] = exception.args[0]
IndexError: tuple index out of range

`

I am also having the same issue. I have the same pipeline structure. Minio works fine but there is a problem with the kubeflow. Here you can find my logs:
`
Uncaught exception in write_error
Traceback (most recent call last):
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/tornado/web.py", line 1704, in _execute
result = await result
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/elyra/pipeline/handlers.py", line 89, in post
response = await PipelineProcessorManager.instance().process(pipeline)
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/elyra/pipeline/processor.py", line 70, in process
res = await asyncio.get_event_loop().run_in_executor(None, processor.process, pipeline)
File "/Users/anaconda3/envs/smartix/lib/python3.8/concurrent/futures/thread.py", line 57, in run
result = self.fn(*self.args, **self.kwargs)
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/elyra/pipeline/processor_kfp.py", line 97, in process
client.upload_pipeline(pipeline_path,
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp/_client.py", line 878, in upload_pipeline
response = self.upload_api.upload_pipeline(pipeline_package_path, name=pipeline_name, description=description)
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 83, in upload_pipeline
return self.upload_pipeline_with_http_info(uploadfile, **kwargs)  # noqa: E501
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api/pipeline_upload_service_api.py", line 177, in upload_pipeline_with_http_info
return self.api_client.call_api(
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 378, in call_api
return self.__call_api(resource_path, method,
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 202, in __call_api
raise e
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 195, in __call_api
response_data = self.request(
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/api_client.py", line 421, in request
return self.rest_client.POST(url,
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/rest.py", line 279, in POST
return self.request("POST", url,
File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/kfp_server_api/rest.py", line 238, in request
raise ApiException(http_resp=r)
kfp_server_api.exceptions.ApiException: (404)
Reason: Not Found
HTTP response headers: HTTPHeaderDict({'x-powered-by': 'Express', 'content-security-policy': "default-src 'none'", 'x-content-type-options': 'nosniff', 'content-type': 'text/html; charset=utf-8', 'content-length': '180', 'date': 'Fri, 22 Jan 2021 15:40:02 GMT', 'x-envoy-upstream-service-time': '1', 'server': 'istio-envoy'})
HTTP response body:

Error

Cannot POST //pipeline/apis/v1beta1/pipelines/upload

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/tornado/web.py", line 1217, in send_error
    self.write_error(status_code, **kwargs)
  File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/elyra/util/http.py", line 64, in write_error
    reply['message'] = exception.args[0]
IndexError: tuple index out of range

`

TypeError:  Parser must be a string or character stream, not dict

@jeff900911 Thank you!  Looks like you  might be running into https://github.com/elyra-ai/elyra/issues/308#issuecomment-594826299

TypeError:  Parser must be a string or character stream, not dict

@jeff900911 Thank you!  Looks like you  might be running into https://github.com/elyra-ai/elyra/issues/308#issuecomment-594826299

@TrubadurOsman Please check your KFP runtime environment configuration in Elyra. The error message seems to indicate that you've configured the KFP API endpoint as http://.../_/pipeline (instead of  http://.../pipeline), which causes the request to fail because the /_/pipeline/apis/v1beta1/pipelines/upload endpoint does not exist.

@TrubadurOsman Please check your KFP runtime environment configuration in Elyra. The error message seems to indicate that you've configured the KFP API endpoint as http://.../_/pipeline (instead of  http://.../pipeline), which causes the request to fail because the /_/pipeline/apis/v1beta1/pipelines/upload endpoint does not exist.

Looks like we should tolerate zero-length args in the exception instance as well:
    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/tornado/web.py", line 1217, in send_error
        self.write_error(status_code, **kwargs)
      File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/elyra/util/http.py", line 64, in write_error
        reply['message'] = exception.args[0]
    IndexError: tuple index out of range

Looks like we should tolerate zero-length args in the exception instance as well:
    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/tornado/web.py", line 1217, in send_error
        self.write_error(status_code, **kwargs)
      File "/Users/anaconda3/envs/smartix/lib/python3.8/site-packages/elyra/util/http.py", line 64, in write_error
        reply['message'] = exception.args[0]
    IndexError: tuple index out of range

Looks like we should tolerate zero-length args in the exception instance as well:

@kevin-bates good catch.   I just opened https://github.com/elyra-ai/elyra/issues/1228 for this specific problem

Looks like we should tolerate zero-length args in the exception instance as well:

@kevin-bates good catch.   I just opened https://github.com/elyra-ai/elyra/issues/1228 for this specific problem

Update: I solved this problem by changing the pipeline URL with baseurl/pipeline and giving namespace to elyra

@TrubadurOsman  Thank you for the update! Do we need to be clearer in our documentation (or the UI) what the valid API endpoint should look like?

Update: I solved this problem by changing the pipeline URL with baseurl/pipeline and giving namespace to elyra

@TrubadurOsman  Thank you for the update! Do we need to be clearer in our documentation (or the UI) what the valid API endpoint should look like?

For future reference (anybody reading this issue), a good way to verify that the provided Kubeflow Pipelines API endpoint is valid is to open the Kubeflow Pipelines UI link that is displayed in the runtime configuration list:

If the link works the provided URL should be correct.
The example URL shown above returns an error

For future reference (anybody reading this issue), a good way to verify that the provided Kubeflow Pipelines API endpoint is valid is to open the Kubeflow Pipelines UI link that is displayed in the runtime configuration list:

If the link works the provided URL should be correct.
The example URL shown above returns an error

Update: I solved this problem by changing the pipeline URL with baseurl/pipeline and giving namespace to elyra

@TrubadurOsman Thank you for the update! Do we need to be clearer in our documentation (or the UI) what the valid API endpoint should look like?

You are welcome. In UI namespace was an optional field but I guess it fails when it is empty. Making it a required field will be better. Also changing the etc/host file for minio was on documentation but it was not shown in the tutorials. It took a bunch of time to realize that problem was due to url name. It would be better if you can strictly mention changing the hosts file for remote deployment on tutorials.

Update: I solved this problem by changing the pipeline URL with baseurl/pipeline and giving namespace to elyra

@TrubadurOsman Thank you for the update! Do we need to be clearer in our documentation (or the UI) what the valid API endpoint should look like?

You are welcome. In UI namespace was an optional field but I guess it fails when it is empty. Making it a required field will be better. Also changing the etc/host file for minio was on documentation but it was not shown in the tutorials. It took a bunch of time to realize that problem was due to url name. It would be better if you can strictly mention changing the hosts file for remote deployment on tutorials.

Assume that @TrubadurOsman has worked past the issue and opened #1692 for follow on


enable text search on all metadata

I'd like to be able to search all the evaluations using a global search input box. for instance, to search for "sea ice" and get matching records.

Would love to, but it's not really useful if we don't have the title of the resource extracted (cf. your other issue)
Also using FAIRsharing FAIR evaluator JSON-LD model creates quite an horrible object to search through, so there are needs to better think the whole implementation of the specifications

can't just text search in mongodb ?

It can already be done on the title / URI using the table filter solution (it's at 1 click of reach)


Resolves #102 and Code Optimizations

I've run it using: GraalVM 21
On the MacBook Pro M2 (16GB) it runs in: 1m34.464s

01:58.536, thx.


[AMS] Fix #12469: adding Fairplay content-key-policy fails due to problems with 'ask' parameter

Issue #12469
When adding the ASK key to Fairplay content-key-policy CLI is expecting a bytearray when it should be expecting a 32 character hexadecimal string.
Reverting the changes made in this PR
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add to S167

@haroldrandom I'm facing the same issue on the node js sdk -- is this a fix that should be ported over to there as well?


在单机环境测试时，当入库数据量达到400W左右出现以下错误

2020-06-23 23:27:37.225270 E | etcdserver: cannot monitor file descriptor usage (open /proc/self/fd: too many open files)
2020-06-23 23:27:37.229599 I | http: Accept error: accept tcp [::]:9001: accept4: too many open files; retrying in 5ms
2020-06-23 23:27:37.237359 I | http: Accept error: accept tcp [::]:9001: accept4: too many open files; retrying in 5ms
2020-06-23 23:27:37.244867 I | http: Accept error: accept tcp [::]:9001: accept4: too many open files; retrying in 5ms
2020-06-23 23:27:37.252076 I | http: Accept error: accept tcp [::]:9001: accept4: too many open files; retrying in 5ms
2020-06-23 23:27:37.261595 I | http: Accept error: accept tcp [::]:9001: accept4: too many open files; retrying in 5ms
2020-06-23 23:27:37.267737 I | http: Accept error: accept tcp [::]:9001: accept4: too many open files; retrying in 10ms
2020-06-23 23:27:40.001118 I | http: Accept error: accept tcp [::]:9001: accept4: too many open files; retrying in 5ms
2020-06-23 23:27:41.030465 I | http: Accept error: accept tcp [::]:9001: accept4: too many open files; retrying in 5ms
2020-06-23 23:27:42.083418 I | http: Accept error: accept tcp [::]:9001: accept4: too many open files; retrying in 5ms
E0623 23:27:42.422599  196316 store_raft_job.go:113] [ERROR] dump index err response code :[4294967295]
E0623 23:27:42.422599  196316 store_raft_job.go:113] [ERROR] dump index err response code :[4294967295]
log: exiting because of error: open log file[/data/server77_data/rrjia/vearch_logs/Master.ERROR.log] err[open /data/server77_data/rrjia/vearch_logs/Master.ERROR.log: too many open files]

文件句柄配置少了。