How to authenticate with BigQuery from Apache Spark (pyspark)?

Question

I have create a client id and client secret for my bigquery project, but I don't know how to use those to successfully save a dataframe from a pyspark script to my bigquery table. My python code below results in the following error. Is there a way I can connect to BigQuery using the save options on the pyspark dataframe?

Code

df.write \
  .format("bigquery") \
  .option("client_id", "<MY_CLIENT_ID>") \
  .option("client_secret", "<MY_CLIENT_SECRET>") \
  .option("project", "bigquery-project-id") \
  .option("table", "dataset.table") \
  .save()

Error

py4j.protocol.Py4JJavaError: An error occurred while calling o93.save. : com.google.cloud.spark.bigquery.repackaged.com.google.cloud.bigquery.BigQueryException: 400 Bad Request { "error": "invalid_grant", "error_description": "Bad Request" } at com.google.cloud.spark.bigquery.repackaged.com.google.cloud.bigquery.spi.v2.HttpBigQueryRpc.translate(HttpBigQueryRpc.java:106) at com.google.cloud.spark.bigquery.repackaged.com.google.cloud.bigquery.spi.v2.HttpBigQueryRpc.getTable(HttpBigQueryRpc.java:268) at com.google.cloud.spark.bigquery.repackaged.com.google.cloud.bigquery.BigQueryImpl$17.call(BigQueryImpl.java:664) at com.google.cloud.spark.bigquery.repackaged.com.google.cloud.bigquery.BigQueryImpl$17.call(BigQueryImpl.java:661) at com.google.cloud.spark.bigquery.repackaged.com.google.api.gax.retrying.DirectRetryingExecutor.submit(DirectRetryingExecutor.java:105) at com.google.cloud.spark.bigquery.repackaged.com.google.cloud.RetryHelper.run(RetryHelper.java:76) at com.google.cloud.spark.bigquery.repackaged.com.google.cloud.RetryHelper.runWithRetries(RetryHelper.java:50) at com.google.cloud.spark.bigquery.repackaged.com.google.cloud.bigquery.BigQueryImpl.getTable(BigQueryImpl.java:660) at com.google.cloud.spark.bigquery.BigQueryInsertableRelation.getTable(BigQueryInsertableRelation.scala:68) at com.google.cloud.spark.bigquery.BigQueryInsertableRelation.exists(BigQueryInsertableRelation.scala:54) at com.google.cloud.spark.bigquery.BigQueryRelationProvider.createRelation(BigQueryRelationProvider.scala:86) at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45) at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70) at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68) at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:86) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131) at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127) at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127) at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80) at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80) at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676) at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676) at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73) at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676) at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:285) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:271) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:282) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:238) at java.lang.Thread.run(Thread.java:748) Caused by: com.google.cloud.spark.bigquery.repackaged.com.google.api.client.http.HttpResponseException: 400 Bad Request { "error": "invalid_grant", "error_description": "Bad Request" }

blackbishop blackbishop · Accepted Answer · 2019-12-06T18:04:26

From spark-bigquery-connector :

How do I authenticate outside GCE / Dataproc?

Use a service account JSON key and GOOGLE_APPLICATION_CREDENTIALS as described here.

Credentials can also be provided explicitly either as a parameter or from Spark runtime configuration. It can be passed in as a base64-encoded string directly, or a file path that contains the credentials (but not both).

So you should be using this:

spark.read.format("bigquery").option("credentialsFile", "</path/to/key/file>")

How to authenticate with BigQuery from Apache Spark (pyspark)?

1 Answers