When using a Talend bigquery input component (BQ java api) to read from bigquery, I get the following error (for a long running job) -
Exception in component tBigQueryInput_4
com.google.api.client.googleapis.json.GoogleJsonResponseException: 404 Not Found
{
"code" : 404,
"errors" : [ {
"domain" : "global",
"message" : "Not found: Table rand-cap:_f000fcf374688fc5e7da50a4c0c04ba228d993c3.anon0849eba05949a62962f218a0433d6ee82bf13a7b",
"reason" : "notFound"
} ],
"message" : "Not found: Table rand-cap:_f000fcf374688fc5e7da50a4c0c04ba228d993c3.anon0849eba05949a62962f218a0433d6ee82bf13a7b"
}
Is this because of the "temporary" table that bq creates when querying results not being available after 24hrs. Or is it because rate limit was exceeded since I am querying a large table ?
In either case, how can I find more details on this error and what steps should I take to prevent this ?
Thank you !
This seems to be a problem in Talend, there are other users describing your issue: https://www.talendforge.org/forum/viewtopic.php?id=44734
Google Bigquery has a property i.e. Allowlargeresults but its not there in TBigqueryinput.
Hi there - I am currently using Talend open studio v6.1.1 and this issue still exists.
Related
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error response :
{
"code" : 403,
"errors" : [ {
"domain" : "usageLimits",
"location" : "user",
"locationType" : "other",
"message" : "User rate limit exceeded",
"reason" : "userRateLimitExceeded"
} ],
"message" : "User rate limit exceeded"
}
User rate limit exceeded
This error is flood protection. Resolve a 403 error: User rate limit exceeded
The solution would be to slow down and implement exponential backoff and retry the request.
I'm trying to connect BigQuery to a BI Tool (Cognos Analytics) through a JDBC driver.
It all works OK, until I try to read a gSheet generated table. Then I get the following error:
Data source adapter error: java.sql.SQLException: [Simba][BigQueryJDBCDriver](100033) Error getting job status.
[Simba][BigQueryJDBCDriver](100033) Error getting job status.
[Simba][BigQueryJDBCDriver](100033) Error getting job status.
400 Bad Request
{
"code" : 400,
"errors" : [ {
"domain" : "global",
"message" : "Error while reading table: <GSHEET-TABLE>, error message: Failed to read the spreadsheet. Error code: PERMISSION_DENIED",
"reason" : "invalid"
} ],
"message" : "Error while reading table: <GSHEET-TABLE>, error message: Failed to read the spreadsheet. Error code: PERMISSION_DENIED",
"status" : "INVALID_ARGUMENT"
}
My connection string is the following:
jdbc:bigquery://https://www.googleapis.com/bigquery/v2:443;ProjectId=<MY-PROJECT-ID>;OAuthType=0;OAuthServiceAcctEmail=<CLIENT-EMAIL-FROM-JSON>;OAuthPvtKeyPath=<PATH-TO-JSON>;Timeout=60; RequestGoogleDriveScope=1;
The Service Account has full Admin ownership of the entire project.
Does somebody know how to access gSheets generated tables?
I am using Cloud Storage Text to BigQuery template on Cloud Composer.
The template is kicked from Python google api client.
The same program
works fine in US location (for Dataflow and BigQuery).
fails in asia-northeast1 location.
works fine with the fewer (less than 10000) input files in asia-northeast location.
Does anybody have an idea about this?
I want to execute in the asia-northeast location for business reason.
More details about failure:
The program worked until "ReifyRenameInput", and the failed .
dataflow job failed
with the error message below:
java.io.IOException: Unable to insert job: beam_load_textiotobigquerydataflow0releaser0806214711ca282fc3_8fca2422ccd74649b984a625f246295c_2a18c21953c26c4d4da2f8f0850da0d2_00000-0, aborting after 9 .
at org.apache.beam.sdk.io.gcp.bigquery.BigQueryServicesImpl$JobServiceImpl.startJob(BigQueryServicesImpl.java:231)
at org.apache.beam.sdk.io.gcp.bigquery.BigQueryServicesImpl$JobServiceImpl.startJob(BigQueryServicesImpl.java:202)
at org.apache.beam.sdk.io.gcp.bigquery.BigQueryServicesImpl$JobServiceImpl.startCopyJob(BigQueryServicesImpl.java:196)
at org.apache.beam.sdk.io.gcp.bigquery.WriteRename.copy(WriteRename.java:144)
at org.apache.beam.sdk.io.gcp.bigquery.WriteRename.writeRename(WriteRename.java:107)
at org.apache.beam.sdk.io.gcp.bigquery.WriteRename.processElement(WriteRename.java:80)
Caused by: com.google.api.client.googleapis.json.GoogleJsonResponseException:
404 Not Found { "code" : 404, "errors" : [ { "domain" : "global", "message" : "Not found: Dataset pj:datasetname", "reason" : "notFound" } ], "message" : "Not found: Dataset pj:datasetname" }
(pj and dataset name are not real name, and they are project name and dataset name for outputTable parameter)
Although the error message said the dataset is not found, the dataset surely existed.
Moreover, some new tables which seems to be tempory tables were created in the dataset after the program.
This is a known issue related to your Beam SDK version according to this public issue tracker. The Beam 2.5.0 SDK version doesn't have this issue.
I'm trying to insert data into BigQuery using the BigQuery Api C# Sdk.
I created a new Job with Json Newline Delimited data.
When I use :
100 lines for inputs : OK
250 lines for inputs : OK
500 lines for inputs : KO
2500 lines : KO
The error encountered is :
"status": {
"state": "DONE",
"errorResult": {
"reason": "invalid",
"message": "Too many errors encountered. Limit is: 0."
},
"errors": [
{
"reason": "internalError",
"location": "File: 0",
"message": "Unexpected. Please try again."
},
{
"reason": "invalid",
"message": "Too many errors encountered. Limit is: 0."
}
]
}
The file works well when I use the Bq Tools with command :
bq load --source_format=NEWLINE_DELIMITED_JSON dataset.datatable pathToJsonFile
Something seems to be wrong on server side or maybe when I transmit the file but we cannot get more log than "internal server error"
Does anyone have more informations on this ?
Thanks you
"Unexpected. Please try again." could either indicate that the contents of the files you provided had unexpected characters, or it could mean that an unexpected internal server condition occurred. There are several questions which might help shed some light on this:
does this consistently happen no matter how many times you retry?
does this directly depend on the lines in the file, or can you construct a simple upload file which doesn't trigger the error condition?
One option to potentially avoid these problems is to send the load job request with configuration.load.maxBadRecords higher than zero.
Feel free to comment with more info and I can maybe update this answer.
Streaming data into BigQuery keeps failing due to the following error, which occurs more frequently recently:
com.google.api.client.googleapis.json.GoogleJsonResponseException: 503 Service Unavailable
{
"code" : 503,
"errors" : [ {
"domain" : "global",
"message" : "Connection error. Please try again.",
"reason" : "backendError"
} ],
"message" : "Connection error. Please try again."
}
at com.google.api.client.googleapis.json.GoogleJsonResponseException.from(GoogleJsonResponseException.java:145)
at com.google.api.client.googleapis.services.json.AbstractGoogleJsonClientRequest.newExceptionOnError(AbstractGoogleJsonClientRequest.java:113)
at com.google.api.client.googleapis.services.json.AbstractGoogleJsonClientRequest.newExceptionOnError(AbstractGoogleJsonClientRequest.java:40)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest$1.interceptResponse(AbstractGoogleClientRequest.java:312)
at com.google.api.client.http.HttpRequest.execute(HttpRequest.java:1049)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(AbstractGoogleClientRequest.java:410)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(AbstractGoogleClientRequest.java:343)
Relevant question references:
Getting high rate of 503 errors with BigQuery Streaming API
BigQuery - BackEnd error when loading from JAVA API
We (the BigQuery team) are looking into your report of increased connection errors. From the internal monitoring, there hasn't been global a spike in connection errors in the last several days. However, that doesn't mean that your tables, specifically, weren't affected.
Connection errors can be tricky to chase down, because they can be caused by errors before they get to the BigQuery servers or after they leave. The more information your can provide, the easier it is for us to diagnose the issue.
The best practice for streaming input is to handle temporary errors like this to retry the request. It can be a little tricky, since when you get a connection error you don't actually know whether the insert succeeded. If you include a unique insertId with your data (see the documentation here), you can safely resend the request (within the deduplication window period, which I think is 15 minutes) without worrying that the same row will get added multiple times.