Reading data from Bigquery External Table using PySpark and create DataFrame

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I have created a NEWLINE DELIM JSON File in GCS. I have created an external table on top of the same JSON file as well and able to read data from BigQuery UI.

I want to access the external table data using PySpark and create a dataframe and then run the same job from Dataproc. Below is the code snippet I've written:

#!/usr/bin/python
import sys
import json
from pyspark.sql.functions import udf, lit, when, date_sub
from pyspark.sql.types import ArrayType, IntegerType, StructType, StructField, StringType, BooleanType, DateType
from pyspark import SparkContext, SparkConf, SQLContext
from pyspark.sql import SparkSession
from pyspark.sql import Row
from datetime import datetime

TargetTableUri=sys.argv[1]

spark = SparkSession \
  .builder \
  .master('yarn') \
  .appName('spark-bigquery-demo') \
  .getOrCreate()


bucket1 = "gs://first-bucket-arpan/output1"
spark.conf.set('temporaryGcsBucket', bucket1)

src_tbl = spark.read.format('bigquery') \
  .option('table', 'turing-thought-277215:first_dataset.ext_employee_details') \
  .load()
src_tbl.createOrReplaceTempView('src_tbl')

src_tbl_df = spark.sql( 'SELECT EMPID,EMPNAME,STREETADRESS,REGION,STATE,COUNTRY FROM src_tbl' )
src_tbl_df.show()
src_tbl_df.print_schema()

While running the job from dataproc cluster, getting below error: ": java.lang.UnsupportedOperationException: The type of table turing-thought-277215.first_dataset.ext_employee_details is currently not supported: EXTERNAL"

Is BigQuery External Table not supported in PySpark for BigQuery Connector? Below is the complete log.

20/08/13 16:44:25 INFO org.spark_project.jetty.util.log: Logging initialized @4863ms
20/08/13 16:44:25 INFO org.spark_project.jetty.server.Server: jetty-9.3.z-SNAPSHOT, build timestamp: unknown, git hash: unknown
20/08/13 16:44:25 INFO org.spark_project.jetty.server.Server: Started @5045ms
20/08/13 16:44:25 INFO org.spark_project.jetty.server.AbstractConnector: Started ServerConnector@5cf22b28{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
20/08/13 16:44:25 WARN org.apache.spark.scheduler.FairSchedulableBuilder: Fair Scheduler configuration file not found so jobs will be scheduled in FIFO order. To use fair scheduling, configure pools in fairscheduler.xml or set spark.scheduler.allocation.file to a file that contains the configuration.
20/08/13 16:44:27 INFO org.apache.hadoop.yarn.client.RMProxy: Connecting to ResourceManager at my-dataproc-cluster-m/10.148.0.40:8032
20/08/13 16:44:27 INFO org.apache.hadoop.yarn.client.AHSProxy: Connecting to Application History server at my-dataproc-cluster-m/10.148.0.40:10200
20/08/13 16:44:31 INFO org.apache.hadoop.yarn.client.api.impl.YarnClientImpl: Submitted application application_1596957621647_0022
Traceback (most recent call last):
  File "/tmp/job-scd2curation-6/scdtype2curation.py", line 25, in <module>
    .option('table', 'turing-thought-277215:first_dataset.ext_employee_details') \
  File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 172, in load
  File "/usr/lib/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
  File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
  File "/usr/lib/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o59.load.

: java.lang.UnsupportedOperationException: The type of table turing-thought-277215.first_dataset.ext_employee_details is currently not supported: EXTERNAL

    at com.google.cloud.spark.bigquery.BigQueryRelationProvider.createRelationInternal(BigQueryRelationProvider.scala:83)
    at com.google.cloud.spark.bigquery.BigQueryRelationProvider.createRelation(BigQueryRelationProvider.scala:40)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:341)
    at org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:239)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:227)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:164)
    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)
google-cloud-dataproc pyspark google-bigquery python
1 Answers

It only support the table and view not the external. See the source

    val table = Option(bigquery.getTable(opts.tableId))
      .getOrElse(sys.error(s"Table $tableName not found"))
    table.getDefinition[TableDefinition].getType match {
      case TABLE => new DirectBigQueryRelation(opts, table)(sqlContext)
      case VIEW | MATERIALIZED_VIEW => if (opts.viewsEnabled) {
        new DirectBigQueryRelation(opts, table)(sqlContext)
      } else {
        sys.error(
          s"""Views were not enabled. You can enable views by setting
             |'${SparkBigQueryOptions.ViewsEnabledOption}' to true.
             |Notice additional cost may occur."""
            .stripMargin.replace('\n', ' '))
      }
      case unsupported => throw new UnsupportedOperationException(
        s"The type of table $tableName is currently not supported: $unsupported")
    }
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