Comments (3)
On spark-shell running DML query run fast, but on spark-submit running in yarn and cluster mode it took almost 2-3 minutes for single query
from spark-bigquery.
This isn't a bug but more of a performance issue, behaviour is very different between a spark shell and spark submit depending on how you are using spark submit
Best to add some form of telemetry to this ticket to validate that it's the connector not yarn or spark adding this overhead
from spark-bigquery.
@samelamin Thanks for your reply, I found that where was issues, it's from spark side
from spark-bigquery.
Related Issues (20)
- class cast exception has occurs (Double cannot be cast to Float) HOT 3
- Using spark-bigquery connector in AWS EMR Zeppelin HOT 4
- java.lang.ClassCastException: java.lang.Long cannot be cast to java.sql.Timestamp HOT 1
- Write to bigquery using DataframeWriter HOT 2
- runDMLQuery on AWS Glue throws an exception because of Jersey libraries conflict HOT 1
- read table second time show error Conflict occurred creating export directory HOT 1
- Error when changing zone to something other than EU/US HOT 3
- Utilize Bigquery Storage API HOT 2
- getting java.lang.NoSuchMethodError on saveAsBigQueryTable HOT 1
- Exception in thread "main" java.lang.NoSuchMethodError: HOT 14
- Struck with error py4j.protocol.Py4JJavaError: An error occurred while calling o39.saveAsBigQueryTable. : java.lang.NoSuchMethodError: com.google.common.base.Preconditions.checkArgument(ZLjava/lang/String;Ljava/lang/Object;Ljava/lang/Object;) HOT 6
- Give content of JSON credentials instead of path to it HOT 2
- Big query export from GCP to AWS S3 using Spark HOT 2
- saveAsBigQueryTable exception with StructType column HOT 1
- Export FS must derive from GoogleHadoopFileSystemBase HOT 1
- writing to bigquery from dataproc HOT 1
- Method saveAsBigQueryTable([class java.lang.String]) does not exist: Issue persists even after shading guava dependecies HOT 4
- Conflict occurred creating export directory already exists HOT 1
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from spark-bigquery.