使用 PySpark 时如何将 jdbc 驱动程序添加到类路径? [英] How to add jdbc drivers to classpath when using PySpark?

问题描述

我如何/在哪里安装 spark sql 的 jdbc 驱动程序?我正在运行 all-spark-notebook docker 镜像，并且我正在尝试将一些数据直接从 sql 数据库中提取到 spark 中.

How / where do I install the jdbc drivers for spark sql? I'm running the all-spark-notebook docker image, and am trying to pull some data directly from a sql database into spark.

据我所知，我需要将驱动程序包含在我的 Classpath 中，我只是不确定如何从 pyspark 中做到这一点?

From what I can tell I can tell I need to include the drivers in my Classpath, I'm just not sure how to do that from pyspark?

from pyspark.sql import SparkSession
spark = SparkSession \
    .builder \
    .master("local") \
    .appName("Python Spark SQL basic example") \
    .getOrCreate()

jdbcDF = spark.read \
    .format("jdbc") \
    .option("url", "jdbc:postgresql:dbserver") \
    .option("dbtable", "jdbc:postgresql:dbserver") \
    .load()

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-2-f3b08ff6d117> in <module>()
      2 spark = SparkSession     .builder     .master("local")     .appName("Python Spark SQL basic example")     .getOrCreate()
      3 
----> 4 jdbcDF = spark.read     .format("jdbc")     .option("url", "jdbc:postgresql:dbserver")     .option("dbtable", "jdbc:postgresql:dbserver")     .load()

/usr/local/spark/python/pyspark/sql/readwriter.py in load(self, path, format, schema, **options)
    163             return self._df(self._jreader.load(self._spark._sc._jvm.PythonUtils.toSeq(path)))
    164         else:
--> 165             return self._df(self._jreader.load())
    166 
    167     @since(1.4)

/usr/local/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in __call__(self, *args)
   1131         answer = self.gateway_client.send_command(command)
   1132         return_value = get_return_value(
-> 1133             answer, self.gateway_client, self.target_id, self.name)
   1134 
   1135         for temp_arg in temp_args:

/usr/local/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
     61     def deco(*a, **kw):
     62         try:
---> 63             return f(*a, **kw)
     64         except py4j.protocol.Py4JJavaError as e:
     65             s = e.java_exception.toString()

/usr/local/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    317                 raise Py4JJavaError(
    318                     "An error occurred while calling {0}{1}{2}.\n".
--> 319                     format(target_id, ".", name), value)
    320             else:
    321                 raise Py4JError(

Py4JJavaError: An error occurred while calling o36.load.
: java.sql.SQLException: No suitable driver
    at java.sql.DriverManager.getDriver(DriverManager.java:315)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions$$anonfun$7.apply(JDBCOptions.scala:84)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions$$anonfun$7.apply(JDBCOptions.scala:84)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:83)
    at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:34)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:32)
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:306)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:178)
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:146)
    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:280)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:214)
    at java.lang.Thread.run(Thread.java:748)

推荐答案

为了包含 postgresql 的驱动程序，您可以执行以下操作:

In order to include the driver for postgresql you can do the following:

conf = SparkConf()  # create the configuration
conf.set("spark.jars", "/path/to/postgresql-connector-java-someversion-bin.jar")  # set the spark.jars

...
spark = SparkSession.builder \
        .config(conf=conf) \  # feed it to the session here
        .master("local") \
        .appName("Python Spark SQL basic example") \
        .getOrCreate()

现在，由于您使用的是 Docker，我猜您必须挂载包含驱动程序 jar 的文件夹并引用挂载的文件夹.(例如:如何在 docker 容器中挂载主机目录?)

Now, since you are using Docker, I guess you have to mount the folder that has the driver jar and refer to the mounted folder. (e.g.: How to mount host directory in docker container?)

希望这会有所帮助，祝你好运！

Hope this helps, good luck!

编辑:另一种方法是在使用 spark-submit 时提供 --driver-class-path 参数，如下所示:

Edit: A diffferent way would be to give the --driver-class-path argument when using spark-submit like this:

spark-submit --driver-class-path=path/to/postgresql-connector-java-someversion-bin.jar file_to_run.py

但我猜这不是你运行它的方式.

but I'm guessing this is not how you will run this.

这篇关于使用 PySpark 时如何将 jdbc 驱动程序添加到类路径?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！