如何在AWS Glue中使用Spark软件包? [英] How to use Spark packages in AWS Glue?

问题描述

我想使用Datastax的

错误:

 文件_write_df_to_cassandra中的文件"/tmp/delta_on_s3_spark.py"，第75行df.write.format(format _).mode('append').options(table = table，keyspace = keyspace).save()保存中的文件"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py"，第732行self._jwrite.save()__call__中的文件"/opt/amazon/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py"，第1257行答案，self.gateway_client，self.target_id，self.name)装饰中的文件"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py"，第63行返回f(* a，** kw)在get_return_value中的第328行中的文件"/opt/amazon/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py"格式(target_id，."，名称)，值)py4j.protocol.Py4JJavaError:调用o84.save时发生错误.:java.lang.NoSuchMethodError:scala.Product.$ init $(Lscala/Product;)V位于com.datastax.spark.connector.TableRef.< init>(TableRef.scala:4)在org.apache.spark.sql.cassandra.DefaultSource $ .TableRefAndOptions(DefaultSource.scala:142)在org.apache.spark.sql.cassandra.DefaultSource.createRelation(DefaultSource.scala:83)...... 

• (根据@alex的评论)将 spark.jars.packages = com.datastax.spark:spark-cassandra-connector_2.12:2.5.1 放在胶水作业的 job参数中

错误:

 文件_write_df_to_cassandra中的文件"/tmp/delta_on_s3_spark.py"，第75行df.write.format(format _).mode('append').options(table = table，keyspace = keyspace).save()保存中的文件"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py"，第732行self._jwrite.save()__call__中的文件"/opt/amazon/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py"，第1257行答案，self.gateway_client，self.target_id，self.name)装饰中的文件"/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py"，第63行返回f(* a，** kw)在get_return_value中的第328行中的文件"/opt/amazon/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py"格式(target_id，."，名称)，值)py4j.protocol.Py4JJavaError:调用o83.save时发生错误.:java.lang.ClassNotFoundException:无法找到数据源:org.apache.spark.sql.cassandra.请在http://spark.apache.org/third-party-projects.html中找到软件包在org.apache.spark.sql.execution.datasources.DataSource $ .lookupDataSource(DataSource.scala:657)在org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:245)在sun.reflect.NativeMethodAccessorImpl.invoke0(本机方法)处...... 

解决方案

推荐的方法是将-packages 或-conf spark.jars.packages 与Maven坐标，因此Spark将正确提取Spark Cassandra Connector(Java驱动程序等)使用的所有必要依赖项-如果仅对SCC jar使用-jars ，则您的工作将失败.

从SCC 2.5.1开始，还有一个新工件-spark-cassandra-connector in AWS Glue. If I run pyspark locally, my command would look like

path/to/spark-3.0.1-bin-hadoop2.7/bin/spark-submit \
--conf spark.cassandra.connection.host=XXX \
--conf spark.cassandra.auth.username=XXX \
--conf spark.cassandra.auth.password=XXX \
--packages com.datastax.spark:spark-cassandra-connector_2.12:2.5.1 \
~/my_script.py

How to run this script in Glue?

---

Things I've tried

• How to import Spark packages in AWS Glue? It looks similar to my question. The accepted answer talks about adding a zipped python module as parameter. But the spark-cassandra-connector isn't a python module.

• (according to @alex's comment) put the SCC assembly in the Glue job's Jar lib path

Error:

    File "/tmp/delta_on_s3_spark.py", line 75, in _write_df_to_cassandra
    df.write.format(format_).mode('append').options(table=table, keyspace=keyspace).save()
  File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 732, in save
    self._jwrite.save()
  File "/opt/amazon/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/opt/amazon/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
    format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o84.save.
: java.lang.NoSuchMethodError: scala.Product.$init$(Lscala/Product;)V
    at com.datastax.spark.connector.TableRef.<init>(TableRef.scala:4)
    at org.apache.spark.sql.cassandra.DefaultSource$.TableRefAndOptions(DefaultSource.scala:142)
    at org.apache.spark.sql.cassandra.DefaultSource.createRelation(DefaultSource.scala:83)
......

• (according to @alex's comment) put spark.jars.packages = com.datastax.spark:spark-cassandra-connector_2.12:2.5.1 in the Glue job's job parameter

Error:

  File "/tmp/delta_on_s3_spark.py", line 75, in _write_df_to_cassandra
    df.write.format(format_).mode('append').options(table=table, keyspace=keyspace).save()
  File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 732, in save
    self._jwrite.save()
  File "/opt/amazon/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/opt/amazon/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
    format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o83.save.
: java.lang.ClassNotFoundException: Failed to find data source: org.apache.spark.sql.cassandra. Please find packages at http://spark.apache.org/third-party-projects.html
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:657)
    at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:245)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
......

解决方案

The recommended way is to use --packages or --conf spark.jars.packages with Maven coordinates, so Spark will correctly pull all necessary dependencies that are used by Spark Cassandra Connector (Java driver, etc.) - if you use --jars with only SCC jar, then your job will fail.

Starting with SCC 2.5.1, there is also a new artifact - spark-cassandra-connector-assembly that includes all necessary dependencies. With it you can avoid problems with conflicting dependencies, plus you can use it with --jars or with Glue job's Jar lib path.

P.S. With Spark 3.0 it's recommended to use SCC 3.0.0-beta, because of significant changes in internals of Spark SQL.

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