Note: this is not (directly) a question about how to print PDF in chrome, instead this is a question about how to get more information when printing fails.
In short: I cannot solve a printing PDF problem, which occurs only for certain (presumably large) pages and could use some assistance in debugging the actual issue.
Background: I am using the chromedriver (v83) and chromium-browser (v83) to print PDF files from webpages by utilizing python selenium. I am building a docker image to contain the required dependencies for this. I have tried to use Debian (buster and stretch) as well as Alpine base images, but all eventually result in the same error, when trying to print some pages. The odd thing is that for other (smaller) pages the printing works, but when many assets and pages are to be printed, the printing fails. I might add that this docker images is eventually being run inside of a Kubernetes cluster, where I assigned up to 4GB of RAM.
What code am I running?
This project was written for python3, so here are some relevant code fragments. Please note that I removed all error handling and waiting for the page loads to complete here.
from selenium import webdriver
appState = {
"recentDestinations": [
{
"id": "Save as PDF",
"origin": "local"
}
],
"selectedDestinationId": "Save as PDF",
"version": 2
}
def get_chrome_options(headless: bool, enable_logging: bool) -> Options:
chrome_options = webdriver.ChromeOptions()
profile = {'printing.print_preview_sticky_settings.appState': json.dumps(appState)}
chrome_options.add_experimental_option('prefs', profile)
if headless:
chrome_options.add_argument('--headless')
chrome_options.add_argument('--no-sandbox')
chrome_options.add_argument('--window-size=1920,1080')
chrome_options.add_argument('--disable-gpu')
chrome_options.add_argument('--disable-web-security')
chrome_options.add_argument('-–allow-file-access-from-files')
chrome_options.add_argument('--run-all-compositor-stages-before-draw')
chrome_options.add_argument('--kiosk-printing')
if enable_logging:
chrome_options.add_argument('--enable-logging')
return chrome_options
def print_the_page(url):
driver = webdriver.Chrome(chrome_options=get_chrome_options(headless, enable_logging))
driver.execute(driver_command=Command.GET, params={'url': url})
command_url = f"{driver.command_executor._url}/session/{driver.session_id}/chromium/send_command_and_get_result"
response = driver.command_executor._request('POST', command_url, json.dumps({'cmd': 'Page.printToPDF', 'params': {}}))
Then what happens?
For some pages this fails - meaning - there is this message in the response:
{'status': 500, 'value': '{"value":{"error":"unknown error","message":"unknown error: unhandled inspector error: {\\"code\\":-32000,\\"message\\":\\"Printing failed\\"}\\n (Session info: headless chrome=83.0.4103.116)","stacktrace":""}}'}
[UPDATE]
I have managed to produce some more error output when using the --print-to-pdf option directly, which seems to hint at an "out-of-memory" issue here:
[0923/135406.102857:WARNING:discardable_shared_memory_manager.cc(194)] Less than 64MB of free space in temporary directory for shared memory files: 23
[0923/135406.110108:WARNING:dns_config_service_posix.cc(341)] Failed to read DnsConfig.
[0923/135406.180892:WARNING:dns_config_service_posix.cc(341)] Failed to read DnsConfig.
[0923/135406.613221:FATAL:memory.cc(38)] Out of memory. size=796176
Received signal 6
r8: 00007fa6f39dadc4 r9: 0000000000000000 r10: 0000000000000008 r11: 0000000000000246
r12: 0000557efd1b0660 r13: 0000000000000000 r14: 00007fa6f39db240 r15: 0000000000000043
di: 0000000000000002 si: 00007fa6f39dac90 bp: 00007fa6f39dac90 bx: 0000000000000000
dx: 0000000000000000 ax: 0000000000000000 cx: 00007fa6fd347a71 sp: 00007fa6f39dac88
ip: 00007fa6fd347a71 efl: 0000000000000246 cgf: 002b000000000033 erf: 0000000000000000
trp: 0000000000000000 msk: 0000000000000000 cr2: 0000000000000000
[end of stack trace]
Calling _exit(1). Core file will not be generated.
[0923/135406.626313:ERROR:headless_shell.cc(399)] Abnormal renderer termination.
I will note here that I have been running this docker container locally on my machine (which has more than enough RAM) as well as on a Kubernetes cluster where this image has requested 4GB RAM. I also monitored the RAM usage and it didn't seem to be an issue - although - that could be illusive if the RAM usage is so radically high that chrome just fails and you never really see that in the overall RAM usage.
[UPDATE 2]
I have tried to use the --print-to-pdf option again, but I am seeing issues with that as well. The resources are loading, but the printing still fails.
│ [0923/144355.169080:ERROR:bus.cc(393)] Failed to connect to the bus: Failed to connect to socket /var/run/dbus/system_bus_socket: No such file or directory
...
│ [0923/141758.393923:WARNING:dns_config_service_posix.cc(341)] Failed to read DnsConfig. │
│ [0923/141758.401925:ERROR:zygote_host_impl_linux.cc(262)] Failed to adjust OOM score of renderer with pid 32: Permission denied (13) │
│ [0923/141758.413475:ERROR:zygote_host_impl_linux.cc(262)] Failed to adjust OOM score of renderer with pid 36: Permission denied (13)
... loading all the resources ...
│ [0923/141824.611661:ERROR:print_render_frame_helper.cc(1889)] Printing failed. │
│ [0923/141824.612439:ERROR:headless_shell.cc(562)] Print to PDF failed
What's the question(s)?
How can I get more information about why the "Printing failed" - unfortunately the "unknown error: unhandled inspector error" hasn't given me any ideas about how to proceed.
Are there potentially any additional flags to get more debug output from chrome or is there a log somewhere that I should be able to find?
What else have I tried?
I have initially been running this under Debian buster with the latest google-chrome and chromium binaries (v85). I have switched to an Alpine base image and chromium - hoping that this might change something, but it didn't.
I have experimented with setting up Xvfb ${DISPLAY} -screen ${SCREEN} ${RESOLUTION} & in Docker, but it didn't seem to have any effect either.
I have tried to switch to using the direct cli google-chrome --print-to-pdf= option, but since it's a page that requires to pass through login authentication, I could only get the login page to print and it also seems to have some not so nice formatting issues.
I have been running this on my machine, outside of Docker, and was able to print as expected, but as soon as I put the same code inside a Docker container, it fails.
Unfortunately, I cannot share the page where this fails with you.
The relevant warning from your logs seems to be this:
[0923/135406.102857:WARNING:discardable_shared_memory_manager.cc(194)] Less than 64MB of free space in temporary directory for shared memory files: 23
The problem appears to stem from Docker's mounted /dev/shm being too small for Chromium to do things like you're trying to do.
I found a closed bug report against chromium referencing this issue in certain limited environments such as AWS Lambda and Docker, it was fixed in chromium v65 behind a command line flag --disable-dev-shm-usage.
The last few comments reference another bug report (now closed) about this issue in chromium v83 where the command line flag was not working properly. It has been fixed in version 84 - per comment 28:
You can find the fix in current stable release of Chrome (version 84.0.4147.89 and above).
You've indicated you're using chromium v83, so you'll need to update at least version 84.0.4147.89, then use the command line flag --disable-dev-shm-usage.
I have installed alfresco & solr in different tomcat instances using below docs url. alfresco share was running file but when i run solr instance and see below error.
http://docs.alfresco.com/5.1/tasks/solr4-install-config.html
generated secure keys for Solr communication.
http://docs.alfresco.com/5.1/tasks/generate-keys-solr4.html
2016-07-18 13:25:30,037 ERROR [solr.tracker.AbstractTracker] [SolrTrackerSche
ler_Worker-14] Tracking failed
org.alfresco.error.AlfrescoRuntimeException: 06180034 api/solr/aclchangesets
turn status:403
at org.alfresco.solr.client.SOLRAPIClient.getAclChangeSets(SOLRAPIClie
.java:162)
at org.alfresco.solr.tracker.AclTracker.checkRepoAndIndexConsistency(A
Tracker.java:335)
at org.alfresco.solr.tracker.AclTracker.trackRepository(AclTracker.jav
313)
at org.alfresco.solr.tracker.AclTracker.doTrack(AclTracker.java:104)
at org.alfresco.solr.tracker.AbstractTracker.track(AbstractTracker.jav
185)
at org.alfresco.solr.tracker.TrackerJob.execute(TrackerJob.java:47)
at org.quartz.core.JobRunShell.run(JobRunShell.java:216)
at org.quartz.simpl.SimpleThreadPool$WorkerThread.run(SimpleThreadPool
ava:563)
2016-07-18 13:25:30,029 ERROR [solr.tracker.AbstractTracker] [SolrTrackerSche
ler_Worker-6] Tracking failed
org.alfresco.error.AlfrescoRuntimeException: 06180033 api/solr/aclchangesets
turn status:403
at org.alfresco.solr.client.SOLRAPIClient.getAclChangeSets(SOLRAPIClie
.java:162)
at org.alfresco.solr.tracker.AclTracker.checkRepoAndIndexConsistency(A
Tracker.java:335)
at org.alfresco.solr.tracker.AclTracker.trackRepository(AclTracker.jav
313)
at org.alfresco.solr.tracker.AclTracker.doTrack(AclTracker.java:104)
at org.alfresco.solr.tracker.AbstractTracker.track(AbstractTracker.jav
185)
at org.alfresco.solr.tracker.TrackerJob.execute(TrackerJob.java:47)
at org.quartz.core.JobRunShell.run(JobRunShell.java:216)
at org.quartz.simpl.SimpleThreadPool$WorkerThread.run(SimpleThreadPool
ava:563)
2016-07-18 13:25:30,056 ERROR [solr.tracker.AbstractTracker] [SolrTrackerSche
ler_Worker-11] Tracking failed
org.alfresco.error.AlfrescoRuntimeException: 06180036 GetModelsDiff return st
us is 403
at org.alfresco.solr.client.SOLRAPIClient.getModelsDiff(SOLRAPIClient.
va:1157)
at org.alfresco.solr.tracker.ModelTracker.trackModelsImpl(ModelTracker
ava:249)
at org.alfresco.solr.tracker.ModelTracker.trackModels(ModelTracker.jav
207)
at org.alfresco.solr.tracker.ModelTracker.doTrack(ModelTracker.java:16
at org.alfresco.solr.tracker.AbstractTracker.track(AbstractTracker.jav
185)
at org.alfresco.solr.tracker.TrackerJob.execute(TrackerJob.java:47)
at org.quartz.core.JobRunShell.run(JobRunShell.java:216)
at org.quartz.simpl.SimpleThreadPool$WorkerThread.run(SimpleThreadPool
ava:563)
I had a similar problem which has been solved by changing
clientAuth="false"
to
clientAuth="want"
in Tomcat 7 server.xml
(credit goes to https://issues.alfresco.com/jira/browse/ACE-4551?focusedCommentId=424920&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-424920)
I am able to successfully run the WordCount example using DataflowPipelineRunner with the maven exec:java command shown in the docs.
However, when I attempt to run it in my own 1.8 VM, it doesn't work. I am using these args (on Windows):
--project=highfive-metrics-service \
--stagingLocation=gs://highfive-dataflow-test/staging \
--runner=BlockingDataflowPipelineRunner \
--gCloudPath=C:/Progra~1/Google/CloudS~1/google-cloud-sdk/bin/gcloud.cmd
I get the following error:
2014-12-24T04:53:34.849Z: (5eada047929dcead): Workflow failed. Causes: (5eada047929dce2e): There was a problem creating the GCE VMs or starting Dataflow on the VMs so no data was processed. Possible causes:
1. A failure in user code on in the worker.
2. A failure in the Dataflow code.
Next Steps:
1. Check the GCE serial console for possible errors in the logs.
2. Look for similar issues on http://stackoverflow.com/questions/tagged/google-cloud-dataflow.
Prior to the subsequent cleanup, I observed three harness instances on GCE as expected. Looking at the serial console for the first one, wordcount-jroy-1224043800-12232038-8cfa-harness-0, I see "normal" (comparing to what I see when running with Maven) looking output that ends with:
Dec 24 04:38:45 [ 16.443484] IPv6: ADDRCONF(NETDEV_CHANGE): docker0: link becomes ready
wordcount-jroy-1224043800-12232038-8cfa-harness-0 kernel: [ 16.438005] IPv6: ADDRCONF(NETDEV_CHANGE): veth30b3796: link becomes ready
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 kernel: [ 16.439395] docker0: port 1(veth30b3796) entered forwarding state
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 kernel: [ 16.440262] docker0: port 1(veth30b3796) entered forwarding state
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 kernel: [ 16.443484] IPv6: ADDRCONF(NETDEV_CHANGE): docker0: link becomes ready
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0
100 12898 100 12898 0 0 2009k 0 --:--:-- --:--:-- --:--:-- 3148k
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: {"attributes":{"config":"{\"alsologtostderr\":true,\"base_task_dir\":\"/tmp/tasks/\",\"commandlines_file_name\":\"commandlines.txt\",\"continue_on_exception\":true,\"dataflow_api_endpoint\":\"https://www.googleapis.com/\",\"dataflow_api_version\":\"v1beta1\",\"log_dir\":\"/dataflow/logs/taskrunner/harness\",\"log_to_gcs\":true,\"log_to_serialconsole\":true,\"parallel_worker_flags\":{\"job_id\":\"2014-12-23_20_38_16.593375-08_10.48.106.68_-469744588\",\"project_id\":\"highfive-metrics-service\",\"reporting_enabled\":true,\"root_url\":\"https://www.googleapis.com/\",\"service_path\":\"dataflow/v1b3/projects/\",\"temp_gcs_directory\":\"gs://highfive-dataflow-test/staging\",\"worker_id\":\"wordcount-jroy-1224043800-12232038-8cfa-harness-0\"},\"project_id\":\"highfive-metrics-service\",\"python_harness_cmd\":\"python_harness_main\",\"scopes\":[\"https://www.googleapis.com/auth/devstorage.full_control\",\"https://www.googleapis.com/auth/cloud-platform\"],\"task_group\":\"nogroup\",\"task_user\":\"nobody\",\"temp_g
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 goo[ 16.494163] device veth29b6136 entered promiscuous mode
gle: cs_directory\":\"gs://highfive-dataflow-test/staging\",\"vm_id\":\"wordcoun[ 16.505311] IPv6: ADDRCONF(NETDEV_UP): veth29b6136: link is not ready
[ 16.507623] docker0: port 2(veth29b6136) entered forwarding state
t-jroy-122404380[ 16.507633] docker0: port 2(veth29b6136) entered forwarding state
0-12232038-8cfa-harness-0\"}","google-container-manifest":"\ncontainers:\n-\n env:\n -\n name: GCS_BUCKET\n value: dataflow-docker-images\n image: google/docker-registry\n imagePullPolicy: PullNever\n name: repository\n ports:\n -\n containerPort: 5000\n hostPort: 5000\n name: registry\n-\n image: localhost:5000/dataflow/taskrunner:20141217-rc00 \n imagePullPolicy: PullIfNotPresent\n name: taskrunner\n volumeMounts:\n -\n mountPath: /dataflow/logs/taskrunner/harness\n name: dataflowlogs-harness\n-\n env:\n -\n name: LOG_DIR\n value: /dataflow/logs\n image: localhost:5000/dataflow/shuffle:20141217-rc00 \n imagePullPolicy: PullIfNotPresent\n name: shuffle\n ports:\n -\n containerPort: 12345\n hostPort: 12345\n name: shuffle1\n -\n containerPort: 22349\n hostPort: 22349\n name: shuffle2\n volumeMounts:\n -\n mountPath: /var/shuffle\n name: dataflow-shuffle\n -\n mountPath: /dataflow/logs\n name: dataflow-logs\nversion: v1
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: beta2\nvolumes:\n-\n name: dataflowlogs-harness\n source:\n hostDir:\n path: /var/log/dataflow/taskrunner/harness\n-\n name: dataflow-shuffle\n source:\n hostDir:\n path: /dataflow/shuffle\n-\n name: dataflow-logs\n source:\n hostDir:\n path: /var/log/dataflow/shuffle\n","job_id":"2014-12-23_20_38_16.593375-08_10.48.106.68_-469744588","packages":"gs://dataflow-releases-prod/worker_packages/NOTICES.shuffle|NOTICES.shuffler|gs://highfive-dataflow-test/staging/access-bridge-64-fE-vq3Wgxy5FvnwmA5YdzQ.jar|access-bridge-64-fE-vq3Wgxy5FvnwmA5YdzQ.jar|gs://highfive-dataflow-test/staging/avro-1.7.7-dTlef6huetK-4IFERNhcqA.jar|avro-1.7.7-dTlef6huetK-4IFERNhcqA.jar|gs://highfive-dataflow-test/staging/charsets-7HC8Y2_U4k8yfkY6e4lxnw.jar|charsets-7HC8Y2_U4k8yfkY6e4lxnw.jar|gs://highfive-dataflow-test/staging/cldrdata-A4PVsm4mesLVUWOTKV5dhQ.jar|cldrdata-A4PVsm4mesLVUWOTKV5dhQ.jar|gs://highfive-dataflow-test/staging/commons-codec-1.3-2I5AW2KkklMQs3emwoFU5Q.jar|commons-codec-1.3-2I5AW2KkklMQs3emwoFU5Q.jar|gs://highfive-dataf
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: low-test/staging/commons-compress-1.4.1-uyvcB16Wfp4wnt8X1Uqi4w.jar|commons-compress-1.4.1-uyvcB16Wfp4wnt8X1Uqi4w.jar|gs://highfive-dataflow-test/staging/commons-logging-1.1.1-blBISC6STJhwBOT8Ksr3NQ.jar|commons-logging-1.1.1-blBISC6STJhwBOT8Ksr3NQ.jar|gs://highfive-dataflow-test/staging/dataflow-test-YIJKUxARCp14MLdWzNdBdQ.zip|dataflow-test-YIJKUxARCp14MLdWzNdBdQ.zip|gs://highfive-dataflow-test/staging/deploy-eLnif2izXW_mrleXudK0Eg.jar|deploy-eLnif2izXW_mrleXudK0Eg.jar|gs://highfive-dataflow-test/staging/dnsns-hmxeUSrhtJou0Wo-UoCjTw.jar|dnsns-hmxeUSrhtJou0Wo-UoCjTw.jar|gs://highfive-dataflow-test/staging/google-api-client-1.19.0-YgeHY_Y9dPd2PwGBWwvmmw.jar|google-api-client-1.19.0-YgeHY_Y9dPd2PwGBWwvmmw.jar|gs://highfive-dataflow-test/staging/google-api-services-bigquery-v2-rev167-1.19.0-mNojB6wqlFqAd2G9Zo7o5w.jar|google-api-services-bigquery-v2-rev167-1.19.0-mNojB6wqlFqAd2G9Zo7o5w.jar|gs://highfive-dataflow-test/staging/google-api-services-compute-v1-rev34-1.19.0-yR5ItN9uOowLPyMiTckyCA.jar|google-api-services
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: -compute-v1-rev34-1.19.0-yR5ItN9uOowLPyMiTckyCA.jar|gs://highfive-dataflow-test/staging/google-api-services-dataflow-v1beta3-rev1-1.19.0-Cg8Pyd4F0t7yqSE4E7v7Rg.jar|google-api-services-dataflow-v1beta3-rev1-1.19.0-Cg8Pyd4F0t7yqSE4E7v7Rg.jar|gs://highfive-dataflow-test/staging/google-api-services-datastore-protobuf-v1beta2-rev1-2.1.0-UxLefoYWxF5K1EpQjKMJ4w.jar|google-api-services-datastore-protobuf-v1beta2-rev1-2.1.0-UxLefoYWxF5K1EpQjKMJ4w.jar|gs://highfive-dataflow-test/staging/google-api-services-pubsub-v1beta1-rev9-1.19.0-7E1jg5ZyfaqZBCHY18fPkQ.jar|google-api-services-pubsub-v1beta1-rev9-1.19.0-7E1jg5ZyfaqZBCHY18fPkQ.jar|gs://highfive-dataflow-test/staging/google-api-services-storage-v1-rev11-1.19.0-8roIrNilTlO2ZqfGfOaqkg.jar|google-api-services-storage-v1-rev11-1.19.0-8roIrNilTlO2ZqfGfOaqkg.jar|gs://highfive-dataflow-test/staging/google-cloud-dataflow-java-examples-all-manual_build-A9j6W_hzOlq6PBrg1oSIAQ.jar|google-cloud-dataflow-java-examples-all-manual_build-A9j6W_hzOlq6PBrg1oSIAQ.jar|gs://highfive-dataf
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: low-test/staging/google-cloud-dataflow-java-examples-all-manual_build-tests-iIdI-AhKWiVKTuJzU5JxcQ.jar|google-cloud-dataflow-java-examples-all-manual_build-tests-iIdI-AhKWiVKTuJzU5JxcQ.jar|gs://highfive-dataflow-test/staging/google-cloud-dataflow-java-sdk-all-alpha-PqdZNVZwhs6ixh6de6vM7A.jar|google-cloud-dataflow-java-sdk-all-alpha-PqdZNVZwhs6ixh6de6vM7A.jar|gs://highfive-dataflow-test/staging/google-http-client-1.19.0-1Vc3U5mogjNLbpTK7NVwDg.jar|google-http-client-1.19.0-1Vc3U5mogjNLbpTK7NVwDg.jar|gs://highfive-dataflow-test/staging/google-http-client-jackson-1.15.0-rc-oW6nFU6Gme53SYGJ9KlNbA.jar|google-http-client-jackson-1.15.0-rc-oW6nFU6Gme53SYGJ9KlNbA.jar|gs://highfive-dataflow-test/staging/google-http-client-jackson2-1.19.0-AOUP2FfuHtACTs_0sul54A.jar|google-http-client-jackson2-1.19.0-AOUP2FfuHtACTs_0sul54A.jar|gs://highfive-dataflow-test/staging/google-http-client-protobuf-1.15.0-rc-xYoprQdNcvzuQGZXvJ3ZaQ.jar|google-http-client-protobuf-1.15.0-rc-xYoprQdNcvzuQGZXvJ3ZaQ.jar|gs://highfive-dataflow-test/st
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: aging/google-oauth-client-1.19.0-b3S5WqgD7iWrwg38pfg3Xg.jar|google-oauth-client-1.19.0-b3S5WqgD7iWrwg38pfg3Xg.jar|gs://highfive-dataflow-test/staging/google-oauth-client-java6-1.19.0-cP8xzICJnsNlhTfaS0egcg.jar|google-oauth-client-java6-1.19.0-cP8xzICJnsNlhTfaS0egcg.jar|gs://highfive-dataflow-test/staging/guava-18.0-HtxcCcuUqPt4QL79yZSvag.jar|guava-18.0-HtxcCcuUqPt4QL79yZSvag.jar|gs://highfive-dataflow-test/staging/hamcrest-all-1.3-n3_QBeS4s5a8ffbBPQIpFQ.jar|hamcrest-all-1.3-n3_QBeS4s5a8ffbBPQIpFQ.jar|gs://highfive-dataflow-test/staging/hamcrest-core-1.3-DvCZoZPq_3EWA4TcZlVL6g.jar|hamcrest-core-1.3-DvCZoZPq_3EWA4TcZlVL6g.jar|gs://highfive-dataflow-test/staging/httpclient-4.0.1-sfocsPjEBE7ppkUpSIJZkA.jar|httpclient-4.0.1-sfocsPjEBE7ppkUpSIJZkA.jar|gs://highfive-dataflow-test/staging/httpcore-4.0.1-_SGEPUOMREqA8u_h7qy9_w.jar|httpcore-4.0.1-_SGEPUOMREqA8u_h7qy9_w.jar|gs://highfive-dataflow-test/staging/idea_rt-6II88e1BKUeCOQqcrZht-w.jar|idea_rt-6II88e1BKUeCOQqcrZht-w.jar|gs://highfive-dataflow-test/staging/jacce
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: ss-laKenN34W6jKKivkBUzVcA.jar|jaccess-laKenN34W6jKKivkBUzVcA.jar|gs://highfive-dataflow-test/staging/jackson-annotations-2.4.2-7cAfM1zz0nmoSOC_NlRIcw.jar|jackson-annotations-2.4.2-7cAfM1zz0nmoSOC_NlRIcw.jar|gs://highfive-dataflow-test/staging/jackson-core-2.4.2-3CV4j5-qI7Y-1EADAiakmw.jar|jackson-core-2.4.2-3CV4j5-qI7Y-1EADAiakmw.jar|gs://highfive-dataflow-test/staging/jackson-core-asl-1.9.13-Ht2i1DaJ57v29KlMROpA4Q.jar|jackson-core-asl-1.9.13-Ht2i1DaJ57v29KlMROpA4Q.jar|gs://highfive-dataflow-test/staging/jackson-databind-2.4.2-M7rkZKQCfOO3vWkOyf9BKg.jar|jackson-databind-2.4.2-M7rkZKQCfOO3vWkOyf9BKg.jar|gs://highfive-dataflow-test/staging/jackson-mapper-asl-1.9.13-eoeZFbovPzo033HQKy6x_Q.jar|jackson-mapper-asl-1.9.13-eoeZFbovPzo033HQKy6x_Q.jar|gs://highfive-dataflow-test/staging/javaws-O8JqID6BpsXsCSRRkhii3w.jar|javaws-O8JqID6BpsXsCSRRkhii3w.jar|gs://highfive-dataflow-test/staging/jce-eMjjWzdqQh30yNZ9HMuXMA.jar|jce-eMjjWzdqQh30yNZ9HMuXMA.jar|gs://highfive-dataflow-test/staging/jfr-xDzacRGMQeIR4SdPe69o1A.jar|jfr
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: -xDzacRGMQeIR4SdPe69o1A.jar|gs://highfive-dataflow-test/staging/jfxrt-5aSYnU7M458Xy_hx5zXF8w.jar|jfxrt-5aSYnU7M458Xy_hx5zXF8w.jar|gs://highfive-dataflow-test/staging/jfxswt-X8I_DFy9gs_6LMLp6_LFPA.jar|jfxswt-X8I_DFy9gs_6LMLp6_LFPA.jar|gs://highfive-dataflow-test/staging/joda-time-2.4-EIO48_0LMn2_imYqUT5jxA.jar|joda-time-2.4-EIO48_0LMn2_imYqUT5jxA.jar|gs://highfive-dataflow-test/staging/jsr305-1.3.9-ntb9Wy3-_ccJ7t2jV2Tb3g.jar|jsr305-1.3.9-ntb9Wy3-_ccJ7t2jV2Tb3g.jar|gs://highfive-dataflow-test/staging/jsse-HOItnWzBlT4hG5HPmlF56w.jar|jsse-HOItnWzBlT4hG5HPmlF56w.jar|gs://highfive-dataflow-test/staging/junit-4.11-lCgz3FeSwzD13Q_KNW4MuQ.jar|junit-4.11-lCgz3FeSwzD13Q_KNW4MuQ.jar|gs://highfive-dataflow-test/staging/localedata-R9ei3T8qar8cibFNN0X7Qg.jar|localedata-R9ei3T8qar8cibFNN0X7Qg.jar|gs://highfive-dataflow-test/staging/management-agent-kiuGeHiVpYKGCDNexcQPIg.jar|management-agent-kiuGeHiVpYKGCDNexcQPIg.jar|gs://highfive-dataflow-test/staging/mockito-all-1.9.5-_T4jPTp05rc7PhcOO34Saw.jar|mockito-all-1.9.5-_T4jPTp0
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: 5rc7PhcOO34Saw.jar|gs://highfive-dataflow-test/staging/nashorn-x8si6abt-U04QaVUHvl_bg.jar|nashorn-x8si6abt-U04QaVUHvl_bg.jar|gs://highfive-dataflow-test/staging/paranamer-2.3-rdmhSrp7GRPVm0JexWjzzg.jar|paranamer-2.3-rdmhSrp7GRPVm0JexWjzzg.jar|gs://highfive-dataflow-test/staging/plugin-TG6U30mOzKi8yMGKYd7ong.jar|plugin-TG6U30mOzKi8yMGKYd7ong.jar|gs://highfive-dataflow-test/staging/protobuf-java-2.5.0-g0LcHblB4cg-bZEbNj3log.jar|protobuf-java-2.5.0-g0LcHblB4cg-bZEbNj3log.jar|gs://highfive-dataflow-test/staging/resources-RavNZwakZf55HEtrC9KyCw.jar|resources-RavNZwakZf55HEtrC9KyCw.jar|gs://highfive-dataflow-test/staging/rt-Z2kDZdIt-eG8CCtFIinW1g.jar|rt-Z2kDZdIt-eG8CCtFIinW1g.jar|gs://highfive-dataflow-test/staging/slf4j-api-1.7.7-M8fOZEWF4TcHiUbfZmJY7A.jar|slf4j-api-1.7.7-M8fOZEWF4TcHiUbfZmJY7A.jar|gs://highfive-dataflow-test/staging/slf4j-jdk14-1.7.7-hDm19oG8Vzi6jVY9pLtr_g.jar|slf4j-jdk14-1.7.7-hDm19oG8Vzi6jVY9pLtr_g.jar|gs://highfive-dataflow-test/staging/snappy-java-1.0.5-WxwEQNTeXiDmEGBuY9O3Og.jar|snappy-java
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: -1.0.5-WxwEQNTeXiDmEGBuY9O3Og.jar|gs://highfive-dataflow-test/staging/sunec-ffsdkJzKsC8XbuZa-XHp3Q.jar|sunec-ffsdkJzKsC8XbuZa-XHp3Q.jar|gs://highfive-dataflow-test/staging/sunjce_provider-4x9-ynTri_pg6Hhk2Zj9Ow.jar|sunjce_provider-4x9-ynTri_pg6Hhk2Zj9Ow.jar|gs://highfive-dataflow-test/staging/sunmscapi-5TwnMDAci3Hf47yMZYmN1g.jar|sunmscapi-5TwnMDAci3Hf47yMZYmN1g.jar|gs://highfive-dataflow-test/staging/sunpkcs11-vCiFLLKN99XBpHW2JTkOBw.jar|sunpkcs11-vCiFLLKN99XBpHW2JTkOBw.jar|gs://highfive-dataflow-test/staging/xz-1.0-6m1HjeacPsPpniZtMte8kw.jar|xz-1.0-6m1HjeacPsPpniZtMte8kw.jar|gs://highfive-dataflow-test/staging/zipfs-SIKQJJIhpGOgSa4tT6nStA.jar|zipfs-SIKQJJIhpGOgSa4tT6nStA.jar"},"description":"GCE Instance created for Dataflow","disks":[{"deviceName":"persistent-disk-0","index":0,"mode":"READ_WRITE","type":"PERSISTENT"}],"hostname":"wordcount-jroy-1224043800-12232038-8cfa-harness-0.c.highfive-metrics-service.internal","id":8960015560553137779,"image":"","machineType":"projects/537312487774/machineTypes/n1-stan
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: dard-4","maintenanceEvent":"NONE","networkInterfaces":[{"accessConfigs":[{"externalIp":"130.211.184.44","type":"ONE_TO_ONE_NAT"}],"forwardedIps":[],"ip":"10.240.173.213","network":"projects/537312487774/networks/default"}],"scheduling":{"automaticRestart":"TRUE","onHostMaintenance":"MIGRATE"},"serviceAccounts":{"537312487774#developer.gserviceaccount.com":{"aliases":["default"],"email":"537312487774#developer.gserviceaccount.com","scopes":["https://www.googleapis.com/auth/any-api","https://www.googleapis.com/auth/bigquery","https://www.googleapis.com/auth/cloud-platform","https://www.googleapis.com/auth/compute","https://www.googleapis.com/auth/datastore","https://www.googleapis.com/auth/devstorage.full_control","https://www.googleapis.com/auth/logging.write","https://www.googleapis.com/auth/ndev.cloudman","https://www.googleapis.com/auth/pubsub","https://www.googleapis.com/auth/userinfo.email"]},"default":{"aliases":["default"],"email":"537312487774#developer.gserviceaccount.com","scopes":["https://www.goog
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: leapis.com/auth/any-api","https://www.googleapis.com/auth/bigquery","https://www.googleapis.com/auth/cloud-platform","https://www.googleapis.com/auth/compute","https://www.googleapis.com/auth/datastore","https://www.googleapis.com/auth/devstorage.full_control","https://www.googleapis.com/auth/logging.write","https://www.googleapis.com/auth/ndev.cloudman","https://www.googleapis.com/auth/pubsub","https://www.googleapis.com/auth/userinfo.email"]}},"tags":["dataflow"],"zone":"projects/537312487774/zones/us-central1-a"}
Dec 24 04:38:45 wordcount-jroy-1224043800-12232038-8cfa-harness-0 google: No startup script found in metadata.
Not sure what I should be looking for, but this seems to reliably fail for me in this manner. I see the same problem when I try to run a custom pipeline of my own (i.e. not WordCount), and also when I run the WordCount example on Linux.
I saved off a file where I recorded:
The complete output from the WordCount main class
The metadata field values set on the GCE instance
The complete serial console output
It is available here.
Things I've tried so far, without success:
Forcing the language level of the compiled classes to 1.7 (am using 1.8 JRE)
Modifying DataflowPipelineRunner::detectClassPathResourcesToStage to not emit JRE jar files (this is a difference I noticed in the log compared to Maven; when running under Maven the JRE jars are not staged).
EDIT: Attempting to set the classpath to EXACTLY the same as what Maven ends up using (removing all of our projects' dependencies). This seemed to change the behavior a bit and I got to a java.lang.ClassNotFoundException: com.google.cloud.dataflow.examples.WordCount$ExtractWordsFn in the worker output.
Strongly suspicious that the problem lies with the staged classpath, but without more specific error messages, I'm shooting in the dark. Would appreciate ideas of where to look next or other things to try.
When running pipelines using [Blocking]DataflowPipelineRunner from the Cloud Dataflow Java SDK, the runner automatically copies everything from your local Java class path to a staging location in Google Cloud Storage, which is being accessed by workers on-demand.
ClassNotFoundException in the Cloud Dataflow worker environment is an indication that required dependencies for your pipeline are not properly staged in a Google Cloud Storage bucket. This likely root cause can be confirmed by looking at the contents of your staging bucket in Google Developers Console and the console output of BlockingDataflowPipelineRunner.
Now, the problem can be fixed by bundling all dependencies into a single, monolithic jar. In Maven, the following command can be used to create such a jar as long as the bundle plugin is properly configured to embed all transitive dependencies:
mvn bundle:bundle
Then, the bundled jar can be executed normally, such as:
java -cp <bundled jar> <main class> --project=<project> ...
Alternatively, the problem can be fixed by manually adding dependencies to your local class path. For example, the following command may be helpful when running an unbundled jar:
java -cp <unbundled jar>:<dep1>:<dep2>:...:<depN> <main class> --project=<project> ...
where dep1 to depN are all the dependencies needed for execution of the program. This is clearly error prone, and we don't endorse it. Our documentation recommends using mvn exec:java because that sets the execution class path automatically from the dependencies listed in the POM file. Specifically, to run WordCount example, use:
mvn exec:java -pl examples \
-Dexec.mainClass=com.google.cloud.dataflow.examples.WordCount \
-Dexec.args="--project=<YOUR GCP PROJECT NAME> --stagingLocation=<YOUR GCS LOCATION> --runner=BlockingDataflowPipelineRunner"
The main difference between bundled and unbundled version is in the upload activity before pipeline submission. Unbundled version has an advantage that it can automatically use unchanged dependencies that may have been uploaded in previous submissions.
To summarize, use mvn exec:java when running an unbundled jar, or bundle the dependencies into a monolithic jar. We'll try to clarify this in the documentation.
There's a very high likelihood that this is an issue with staging dependencies.
There's a high probability if you create a bundled jar it will just work. You can create a bundled jar by running the command
mvn bundle:bundle
This will create a single jar that should pull in all dependencies transitively. You then just need to add that jar to your class path and Dataflow should automatically stage it; Thereby ensuring your code as well as any dependencies are available on the worker.
Most likely the job worked with mvn exec, because maven automatically generates a class path with all dependencies from the POM. When running manually, that doesn't happen. i.e if you invoke java directly e.g.
java -cp <JAR FILES> your.main.class --project=<YOUR PROJECT> ....
then you must add all dependencies to the class path so that they get staged. Creating a bundled jar as suggested above is usually the easiest way to do that.
My suggestion would be to look at the worker logs to see if we can find additional information about what's going on in the workers.
There are three ways to get this information. The first is via the Dataflow UI. Go to the Google Cloud Console and then select the Dataflow option in the left hand frame. You should see a list of your jobs. You can click on the job in question. This should show you a graph of your job. On the right side you should see a button "view logs". Please click that. You should then see a UI for navigating the logs and you can look for errors.
The second option is to look for the logs on GCS. The location to look for is:
gs://PATH TO YOUR STAGING DIRECTORY/logs/JOB-ID/VM-ID/LOG-FILE
You might see multiple log files. The one we are most interested in is the one that starts with "start_java_worker". If that log file doesn't exist then the worker didn't make enough progress to actually upload the file; or else there might have been a permission problem uploading the log file.
In that case the best thing to do is to try to ssh into one of the VMs before it gets torn down. You should have about 15 minutes before the job fails and the VMs are deleted.
Once you login to the VM you can find all the logs in
/var/log/dataflow/...
The log we care most about at this point is:
/var/log/dataflow/taskrunner/harness/start_java_worker-SOME ID.log
If there is a problem starting the code that runs on the VM that log should tell us. That log and the other logs should also tell us if there is a permission problem that prevents the code running on the worker from being able to access Dataflow.
Please take a look and let us know if you find anything.
I struggling to get the "Musicbrainz" data set running on my local machine (MacBook Air, Mountain Lion).
What I did? (Basically what the video said)
Downloaded data set directly from http://www.neo4j.org/develop/example_data
Downloaded fresh Neo4j-Community-2.1.5
Extracted the data set, renamed it to graph.db and copied to /neo4j-community-2.1.5/data/graph.db
Run the server: ./bin/neo4j console, but neo does not start - not even an exception is thrown!!!!
Gerardos-MacBook-Air:neo4j-community-2.1.5 Gery$ ./bin/neo4j console
WARNING: Max 256 open files allowed, minimum of 40 000 recommended.
See the Neo4j manual. Starting Neo4j Server console-mode... Using
additional JVM arguments: -server -XX:+DisableExplicitGC
-Dorg.neo4j.server.properties=conf/neo4j-server.properties -Djava.util.logging.config.file=conf/logging.properties -Dlog4j.configuration=file:conf/log4j.properties -XX:+UseConcMarkSweepGC -XX:+CMSClassUnloadingEnabled 2014-10-09 15:40:31.700+0000 INFO [API] Setting startup timeout to: 120000ms
based on -1 Detected incorrectly shut down database, performing
recovery..
I tried several settings in neo4j.properties, but nothing, see properties below ...
use_memory_mapped_buffers=true
neostore.nodestore.db.mapped_memory=300M
neostore.relationshipstore.db.mapped_memory=3G
neostore.propertystore.db.mapped_memory=500M
neostore.propertystore.db.strings.mapped_memory=500M
neostore.propertystore.db.arrays.mapped_memory=0M
neostore.propertystore.db.index.keys.mapped_memory=15M
neostore.propertystore.db.index.mapped_memory=15M
allow_store_upgrade=true
I was hoping that this would work out of the box. What am I missing ...?
Tried starting neo4j service and got a message like
WARNING: Detected a limit of 1024 for maximum open files, while a
minimum value of 40000 is recommended.
WARNING: Problems with the
operation of the server may occur. Please refer to the Neo4j manual
regarding lifting this limitation. Starting Neo4j Server...
WARNING:
not changing user process [17348]... waiting for server to be
ready... BAD. Neo4j Server may have failed to start, please check the
logs.
The log says :
Opened [/home/ub/graph_db/neo4j-community-1.7.M01/data/graph.db/nioneo_logical.log.1] clean empty log, version=224, lastTxId=654769
2013-03-14 11:26:28.111+0000: TM opening log: /home/ub/graph_db/neo4j-community-1.7.M01/data/graph.db/tm_tx_log.1
2013-03-14 11:26:28.159+0000: Failed to load index provider lucene Target file[lucene.log.v318] already exists
org.neo4j.graphdb.NotFoundException: Target file[lucene.log.v318] already exists
at org.neo4j.kernel.impl.util.FileUtils.renameFile(FileUtils.java:165)
at org.neo4j.kernel.DefaultFileSystemAbstraction.renameFile(DefaultFileSystemAbstraction.java:78)
at org.neo4j.kernel.impl.transaction.xaframework.XaLogicalLog.renameLogFileToRightVersion(XaLogicalLog.java:700)
at org.neo4j.kernel.impl.transaction.xaframework.XaLogicalLog.renameIfExists(XaLogicalLog.java:219)
at org.neo4j.kernel.impl.transaction.xaframework.XaLogicalLog.open(XaLogicalLog.java:171)
at org.neo4j.kernel.impl.transaction.xaframework.XaContainer.openLogicalLog(XaContainer.java:64)
at org.neo4j.index.impl.lucene.LuceneDataSource.<init>(LuceneDataSource.java:229)
at org.neo4j.index.lucene.LuceneIndexProvider.load(LuceneIndexProvider.java:71)
at org.neo4j.kernel.AbstractGraphDatabase$DefaultKernelExtensionLoader.loadIndexImplementations(AbstractGraphDatabase.java:986)
at org.neo4j.kernel.AbstractGraphDatabase$DefaultKernelExtensionLoader.init(AbstractGraphDatabase.java:958)
at org.neo4j.kernel.LifeSupport$LifecycleInstance.init(LifeSupport.java:362)
at org.neo4j.kernel.LifeSupport.init(LifeSupport.java:76)
at org.neo4j.kernel.LifeSupport.start(LifeSupport.java:110)
at org.neo4j.kernel.AbstractGraphDatabase.run(AbstractGraphDatabase.java:178)
at org.neo4j.kernel.EmbeddedGraphDatabase.<init>(EmbeddedGraphDatabase.java:69)
at org.neo4j.server.NeoServerBootstrapper$1.createDatabase(NeoServerBootstrapper.java:65)
at org.neo4j.server.database.Database.createDatabase(Database.java:80)
at org.neo4j.server.database.Database.<init>(Database.java:63)
at org.neo4j.server.NeoServerWithEmbeddedWebServer.startDatabase(NeoServerWithEmbeddedWebServer.java:186)
at org.neo4j.server.NeoServerWithEmbeddedWebServer.start(NeoServerWithEmbeddedWebServer.java:97)
at org.neo4j.server.Bootstrapper.start(Bootstrapper.java:87)
at org.neo4j.server.Bootstrapper.main(Bootstrapper.java:52)
2013-03-14 11:26:28.160+0000: TM shutting down
2013-03-14 11:26:28.382+0000: Closed log /home/biju/graph_db/neo4j-community-1.7.M01/data/graph.db/nioneo_logical.log
2013-03-14 11:26:28.945+0000: NeoStore closed
2013-03-14 11:26:28.946+0000: --- SHUTDOWN diagnostics START ---
2013-03-14 11:26:28.947+0000: --- SHUTDOWN diagnostics END ---
This started happening when I have installed ElasticSearch on my machine. There was one issue with starting Elastic search "JAVA_HOME issue", which is sorted.
I had such a problem when I was installing Neo4j the first time on my Linux laptop, I solved putting this couple of rows at the end of the /etc/security/limits.conf file:
user hard nofile 100000
user soft nofile 40000
where user is the login name of the user who starts Neo4j.
The 10000 and 40000 are somewhat arbirtrary, they were ok for me, in case you still get the error try to increase them.
If you've got a db with that problem, upgrading won't make it go away. 1.8.2 will prevent this from happening though. You're running community I see so keeping old logs around isn't all that necessary. Try deleting the existing lucene.log.v318 file, or move it away at least and see what happens the next startup.