如何使用Spark Dataset写入PostgreSQL hstore

Question

我正在尝试将Spark数据集编写到现有的postgresql表中(不能像列类型那样更改表元数据).这个表的一个列是HStore类型,它会造成麻烦.

当我启动写入时,我看到以下异常(这里原始地图是空的,当转义时给出一个空字符串):

Caused by: java.sql.BatchUpdateException: Batch entry 0 INSERT INTO part_d3da09549b713bbdcd95eb6095f929c8 (.., "my_hstore_column", ..) VALUES (..,'',..) was aborted.  Call getNextException to see the cause.
    at org.postgresql.jdbc.BatchResultHandler.handleError(BatchResultHandler.java:136)
    at org.postgresql.core.v3.QueryExecutorImpl$1.handleError(QueryExecutorImpl.java:419)
    at org.postgresql.core.v3.QueryExecutorImpl$ErrorTrackingResultHandler.handleError(QueryExecutorImpl.java:308)
    at org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:2004)
    at org.postgresql.core.v3.QueryExecutorImpl.flushIfDeadlockRisk(QueryExecutorImpl.java:1187)
    at org.postgresql.core.v3.QueryExecutorImpl.sendQuery(QueryExecutorImpl.java:1212)
    at org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:351)
    at org.postgresql.jdbc.PgStatement.executeBatch(PgStatement.java:1019)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:222)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:300)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:299)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$28.apply(RDD.scala:902)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$28.apply(RDD.scala:902)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1899)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
    at org.apache.spark.scheduler.Task.run(Task.scala:86)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
Caused by: org.postgresql.util.PSQLException: ERROR: column "my_hstore_column" is of type hstore but expression is of type character varying

这就是我这样做的方式:

def escapePgHstore[A, B](hmap: Map[A, B]) = {
  hmap.map{case(key, value) => s""" "${key}"=>${value} """}.mkString(",")
}
...
val props = new Properties()
props.put("user", "xxxxxxx")
props.put("password", "xxxxxxx")

ds.withColumn("my_hstore_column", escape_pg_hstore_udf($"original_column"))
  .drop("original_column")
  .coalesce(1).write
  .mode(org.apache.spark.sql.SaveMode.Append)
  .option("driver", "org.postgresql.Driver")
  .jdbc(jdbcUrl, hashedTablePartName, props)

如果我没有original_column从Map [String,Long] 转义为String,escapePgHstore我会看到以下错误:

java.lang.IllegalArgumentException: Can't get JDBC type for map<string,bigint>
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$getJdbcType$2.apply(JdbcUtils.scala:137)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$getJdbcType$2.apply(JdbcUtils.scala:137)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$getJdbcType(JdbcUtils.scala:136)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$7.apply(JdbcUtils.scala:293)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$7.apply(JdbcUtils.scala:292)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
    at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
    at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
    at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)
    at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.saveTable(JdbcUtils.scala:292)
    at org.apache.spark.sql.DataFrameWriter.jdbc(DataFrameWriter.scala:441)
    at scala.Function0$class.apply$mcV$sp(Function0.scala:34)
    at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
    at scala.App$$anonfun$main$1.apply(App.scala:76)
    at scala.App$$anonfun$main$1.apply(App.scala:76)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
    at scala.App$class.main(App.scala:76)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:736)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:185)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

什么是使spark写出有效的hstore数据类型的正确方法？

Answer 1

事实证明我只是让postgres尝试猜测我的列的适当类型.通过设置stringtype于unspecified连接字符串中的描述的正式文件.

props.put("stringtype", "unspecified")

现在它完美运作!!