Apache spark 如何将MariaDB Connector/J与Pyspark一起用于JDBC？
我在Ubuntu18.04上使用PySpark3.0.1，希望使用JDBC将数据导出到MariaDB服务器 我在pyspark命令行上指定Connector/jjar，如下所示：Apache spark 如何将MariaDB Connector/J与Pyspark一起用于JDBC？,apache-spark,jdbc,pyspark,mariadb,mariadb-connect-engine,Apache Spark,Jdbc,Pyspark,Mariadb,Mariadb Connect Engine,我在Ubuntu18.04上使用PySpark3.0.1，希望使用JDBC将数据导出到MariaDB服务器 我在pyspark命令行上指定Connector/jjar，如下所示： $pyspark--jars/usr/share/java/mariadb java client.jar 但是，当我尝试使用JDBC连接时，会出现以下错误： >>> df1 = sc.parallelize([[1,2,3], [2,3,4]]).toDF(("a", "
$pyspark--jars/usr/share/java/mariadb java client.jar>>> df1 = sc.parallelize([[1,2,3], [2,3,4]]).toDF(("a", "b", "c"))
>>> df1.write.format("jdbc") \
... .mode("overwrite") \
... .option("url", "jdbc:mariadb://localhost:3306/testDatabase?user=foo&password=bar") \
... .option("dbtable", "example") \
... .save()
Traceback (most recent call last):
File "<stdin>", line 4, in <module>
File "/opt/spark/python/pyspark/sql/readwriter.py", line 825, in save
self._jwrite.save()
File "/opt/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 1305, in __call__
File "/opt/spark/python/pyspark/sql/utils.py", line 128, in deco
return f(*a, **kw)
File "/opt/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py", line 328, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o60.save.
: java.sql.SQLException: No suitable driver
at java.sql.DriverManager.getDriver(DriverManager.java:315)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.$anonfun$driverClass$2(JDBCOptions.scala:105)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCOptions.<init>(JDBCOptions.scala:105)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcOptionsInWrite.<init>(JDBCOptions.scala:194)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcOptionsInWrite.<init>(JDBCOptions.scala:198)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcRelationProvider.createRelation(JdbcRelationProvider.scala:45)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$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:90)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:175)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:213)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:210)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:171)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:122)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:121)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:963)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:100)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:87)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:764)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:963)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:415)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:399)
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)
>>>
由于
java.sql.SQLException:没有合适的驱动程序driverorg.mariadb.jdbc.driverdf1.write.format("jdbc") \
.mode("overwrite") \
.option("driver", "org.mariadb.jdbc.Driver") \
.option("url", "jdbc:mysql://localhost:3306/testDatabase?user=foo&password=bar") \
.option("dbtable", "example") \
.save()
请参阅文档中的。在编写以下内容时，您需要使用
驱动程序选项指定mariadb驱动程序类org.mariadb.jdbc.driver
：
df1.write.format("jdbc") \
.mode("overwrite") \
.option("driver", "org.mariadb.jdbc.Driver") \
.option("url", "jdbc:mysql://localhost:3306/testDatabase?user=foo&password=bar") \
.option("dbtable", "example") \
.save()
请参阅文档中的。对于仍面临此错误的任何人
在url中使用mysql，而不是mariadb
jdbc url应该类似于jdbc:mysql:{host}…
，而不是jdbc:mariadb:{host}…
对于仍然面临此错误的任何人
在url中使用mysql，而不是mariadb
jdbc url应该类似于jdbc:mysql:{host}…
而不是jdbc:mariadb:{host}…
示例现在抛出以下错误：java.sql.SQLSyntaxErrorException:（conn=34）您的sql语法有错误；检查与您的MariaDB服务器版本对应的手册，以了解在第1行“a”BIGINT，“b”BIGINT，“c”BIGINT）附近使用的正确语法
还不确定这有什么问题，但显然已经解决了驱动程序设置问题，并从MariaDB处返回了错误。谢谢修复：我需要url为jdbc:mysql:…
notjdbc:mariadb:…
示例现在抛出以下错误：java.sql.SQLSyntaxErrorException:（conn=34）您的sql中有一个错误