我在 Azure 上有一个 Greenplum 集群，我正在尝试通过本地计算机上的 Spark 连接到该集群(使用 Pivotal Greenplum Spark 连接器)。
我在我的 scala 代码中做了类似的事情:
var options = Map[String, String]()
options += ("url" -> url)
options += ("user" -> credential("user"))
options += ("password" -> credential("password"))
options += ("partitionColumn" -> partitionColumn)
sqlContext.read.format("greenplum").options(options).load()
出于测试目的，我创建了一个用户:
DROP USER IF EXISTS user1;
CREATE USER user1 CREATEEXTTABLE (type='writable') PASSWORD 'p@ss0rd';
然后使用该用户创建数据库/表，如下所示
drop table if exists sample;
create table public.sample (id serial, big bigint, wee smallint, stuff text) distributed by (id) ;
insert into sample (big) values (generate_series(1,100));
update sample set wee = 0;
update sample set wee = 1 where mod(id,7)=1;
update sample set stuff = substr('abcdefghijklmnopqrstuvwxyz',1,mod(wee,13));
现在，当我使用 Greenplum 凭据执行 Spark 代码时，(在 Debug模式下运行时)代码似乎成功读取表元数据(它获取列和类型)，但读取行失败并显示 SQLSTATE( 08006)，错误代码(0)。这是堆栈跟踪:
2020-03-24 19:04:31,168 WARN [Executor task launch worker for task 0] com.zaxxer.hikari.pool.ProxyConnection - HikariPool-1 - Connection org.postgresql.jdbc.PgConnection@14fab679 marked as broken because of SQLSTATE(08006), ErrorCode(0)
org.postgresql.util.PSQLException: ERROR: error when writing data to gpfdist http://127.0.0.1:60352/spark_e0aa1f0c8646f023_fffec8bf08e0054d_driver_261, quit after 8 tries (seg1 172.21.0.4:6001 pid=25909)
at org.postgresql.core.v3.QueryExecutorImpl.receiveErrorResponse(QueryExecutorImpl.java:2310)
at org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:2023)
at org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:217)
at org.postgresql.jdbc.PgStatement.execute(PgStatement.java:421)
at org.postgresql.jdbc.PgStatement.executeWithFlags(PgStatement.java:318)
at org.postgresql.jdbc.PgStatement.executeUpdate(PgStatement.java:294)
at com.zaxxer.hikari.pool.ProxyStatement.executeUpdate(ProxyStatement.java:120)
at com.zaxxer.hikari.pool.HikariProxyStatement.executeUpdate(HikariProxyStatement.java)
at io.pivotal.greenplum.spark.jdbc.Jdbc$$anonfun$2.apply(Jdbc.scala:81)
at io.pivotal.greenplum.spark.jdbc.Jdbc$$anonfun$2.apply(Jdbc.scala:79)
at resource.AbstractManagedResource$$anonfun$5.apply(AbstractManagedResource.scala:88)
at scala.util.control.Exception$Catch$$anonfun$either$1.apply(Exception.scala:125)
at scala.util.control.Exception$Catch$$anonfun$either$1.apply(Exception.scala:125)
at scala.util.control.Exception$Catch.apply(Exception.scala:103)
at scala.util.control.Exception$Catch.either(Exception.scala:125)
at resource.AbstractManagedResource.acquireFor(AbstractManagedResource.scala:88)
at resource.ManagedResourceOperations$class.apply(ManagedResourceOperations.scala:26)
at resource.AbstractManagedResource.apply(AbstractManagedResource.scala:50)
at resource.DeferredExtractableManagedResource$$anonfun$tried$1.apply(AbstractManagedResource.scala:33)
at scala.util.Try$.apply(Try.scala:192)
at resource.DeferredExtractableManagedResource.tried(AbstractManagedResource.scala:33)
at io.pivotal.greenplum.spark.jdbc.Jdbc$.copyTable(Jdbc.scala:83)
at io.pivotal.greenplum.spark.externaltable.GreenplumRowIterator.liftedTree1$1(GreenplumRowIterator.scala:105)
at io.pivotal.greenplum.spark.externaltable.GreenplumRowIterator.<init>(GreenplumRowIterator.scala:104)
at io.pivotal.greenplum.spark.GreenplumRDD.compute(GreenplumRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:337)
at org.apache.spark.rdd.RDD$$anonfun$7.apply(RDD.scala:335)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1165)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1156)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:1091)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1156)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:882)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:286)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
我尝试在 Azure 上的 Greenplum 集群上打开端口，但这没有帮助
有什么线索吗？
最佳答案
Spark连接器在每个Spark工作节点上启动一个gpfdist服务器，确定运行工作的机器的地址/主机名并将其报告给Greenplum，以便Greenplum可以向其发送数据。在您的情况下，此解析为 127.0.0.1，因为您在本地计算机上运行，并且 Azure 上的 Greenplum 无法连接到 http://127.0.0.1:60352 上的 gpfdist 服务器。
要实现此功能，必须可以通过可路由的 IP 地址或 DNS 可解析的主机名从 Azure 访问您的 Spark 工作线程。您可以通过指定此处描述的选项来指定是使用主机名还是 IP 地址(以及使用哪个网络接口(interface)来获取 IP 地址):https://greenplum-spark.docs.pivotal.io/1-6/using_the_connector.html#addrcfg
关于scala - Greenplum Spark 连接器 org.postgresql.util.PSQLException : ERROR: error when writing data to gpfdist，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/60842275/