[ https://issues.apache.org/jira/browse/SPARK-28563?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Vishal Donderia resolved SPARK-28563. ------------------------------------- Resolution: Not A Bug > Spark 2.4 | Reading all the data inside partition like directory. > ------------------------------------------------------------------- > > Key: SPARK-28563 > URL: https://issues.apache.org/jira/browse/SPARK-28563 > Project: Spark > Issue Type: Bug > Components: Input/Output > Affects Versions: 2.4.1 > Reporter: Vishal Donderia > Priority: Blocker > > We have upgraded your cluster from Spark 2.3 to 2.4 and currently, we are > observing different behavior while reading data. > > In Spark 2.3 > spark.read.('basePath','output/model').orc('output/model/abc=4') > Expected: We will get "abc" column in schema > Similarly: > spark.read.('basePath','output/model/abc=4').orc('output/model/abc=4') > Expected : It will only read data inside parition abc=4 and abc will not be > part of schema even "output/model" has different schema of files inside > In Spark2.4 > spark.read.('basePath','output/model/abc=4').orc('output/model/abc=4') > It is trying to get the schema from "output/model/" instead of > output/model/abc=4 and job is getting failed because of different schema > {code} > For partitioned table directories, data files should only live in leaf > directories. > And directories at the same level should have the same partition column name. > Please check the following directories for unexpected files or inconsistent > partition column names: > at scala.Predef$.assert(Predef.scala:170) > at > org.apache.spark.sql.execution.datasources.PartitioningUtils$.resolvePartitions(PartitioningUtils.scala:364) > at > org.apache.spark.sql.execution.datasources.PartitioningUtils$.parsePartitions(PartitioningUtils.scala:165) > at > org.apache.spark.sql.execution.datasources.PartitioningUtils$.parsePartitions(PartitioningUtils.scala:100) > at > org.apache.spark.sql.execution.datasources.PartitioningAwareFileIndex.inferPartitioning(PartitioningAwareFileIndex.scala:131) > at > org.apache.spark.sql.execution.datasources.InMemoryFileIndex.partitionSpec(InMemoryFileIndex.scala:71) > at > org.apache.spark.sql.execution.datasources.PartitioningAwareFileIndex.partitionSchema(PartitioningAwareFileIndex.scala:50) > at > org.apache.spark.sql.execution.datasources.DataSource.getOrInferFileFormatSchema(DataSource.scala:144) > at > org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:373) > at > org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:223) > at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:211) > at org.apache.spark.sql.DataFrameReader.orc(DataFrameReader.scala:662) > 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:745) > {code} > > > -- This message was sent by Atlassian JIRA (v7.6.14#76016) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org