我正在尝试加载使用Spark SQL创建的托管蜂巢表。
SparkConf conf = new SparkConf().setAppName(ConnectionTest.class.getName()).setMaster(master);
JavaSparkContext context = new JavaSparkContext(conf);
SQLContext sqlContext = new HiveContext(context);
sqlContext.sql("SELECT * FROM schema.tableName").show(20);
但是我遇到了这个错误：
Exception in thread "main" java.lang.RuntimeException: serious problem
at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.generateSplitsInfo(OrcInputFormat.java:1021)
at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.getSplits(OrcInputFormat.java:1048)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
at org.apache.spark.rdd.HadoopRDD$HadoopMapPartitionsWithSplitRDD.getPartitions(HadoopRDD.scala:381)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
at scala.Option.getOrElse(Option.scala:120)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:190)
at org.apache.spark.sql.execution.Limit.executeCollect(basicOperators.scala:165)
at org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(SparkPlan.scala:174)
at org.apache.spark.sql.DataFrame$$anonfun$org$apache$spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1499)
at org.apache.spark.sql.DataFrame$$anonfun$org$apache$spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1499)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
at org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:2086)
at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$execute$1(DataFrame.scala:1498)
at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$collect(DataFrame.scala:1505)
at org.apache.spark.sql.DataFrame$$anonfun$head$1.apply(DataFrame.scala:1375)
at org.apache.spark.sql.DataFrame$$anonfun$head$1.apply(DataFrame.scala:1374)
at org.apache.spark.sql.DataFrame.withCallback(DataFrame.scala:2099)
at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1374)
at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1456)
at org.apache.spark.sql.DataFrame.showString(DataFrame.scala:170)
at org.apache.spark.sql.DataFrame.show(DataFrame.scala:350)
at org.apache.spark.sql.DataFrame.show(DataFrame.scala:311)
at com.daimler.dbdp.spark.ConnectionTest.run(ConnectionTest.java:45)
at com.daimler.dbdp.spark.ConnectionTest.main(ConnectionTest.java:26)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.NullPointerException
at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$BISplitStrategy.getSplits(OrcInputFormat.java:560)
at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.generateSplitsInfo(OrcInputFormat.java:1010)
... 49 more
似乎与兽人格式有关。当使用兽人格式时，访问Hive Table的最佳方法是什么？
谢谢!!!
火花1.6.2。Java 8hortonworks dist。
您可以尝试在Spark
中设置以下参数scala> sql("set spark.sql.hive.convertMetastoreOrc=true")
// output = res3: org.apache.spark.sql.DataFrame = [key: string, value: string]
然后在Spark中执行查询。
如果在上述参数之后也面临问题，则可以尝试设置以下param。
scala> sql("set spark.sql.orc.impl=native")
// output = res4: org.apache.spark.sql.DataFrame = [key: string, value: string]