Read response from Cheng Lian <lian.cs....@gmail.com> on Aug/27th - it
looks the same problem.
Workarounds
1. write that parquet file in Spark;
2. upgrade to Spark 1.5.
--
Ruslan Dautkhanov
On Mon, Sep 7, 2015 at 3:52 PM, Alex Kozlov <ale...@gmail.com> wrote:
> No, it was created in Hive by CTAS, but any help is appreciated...
>
> On Mon, Sep 7, 2015 at 2:51 PM, Ruslan Dautkhanov <dautkha...@gmail.com>
> wrote:
>
>> That parquet table wasn't created in Spark, is it?
>>
>> There was a recent discussion on this list that complex data types in
>> Spark prior to 1.5 often incompatible with Hive for example, if I remember
>> correctly.
>> On Mon, Sep 7, 2015, 2:57 PM Alex Kozlov <ale...@gmail.com> wrote:
>>
>>> I am trying to read an (array typed) parquet file in spark-shell (Spark
>>> 1.4.1 with Hadoop 2.6):
>>>
>>> {code}
>>> $ bin/spark-shell
>>> log4j:WARN No appenders could be found for logger
>>> (org.apache.hadoop.metrics2.lib.MutableMetricsFactory).
>>> log4j:WARN Please initialize the log4j system properly.
>>> log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig
>>> for more info.
>>> Using Spark's default log4j profile:
>>> org/apache/spark/log4j-defaults.properties
>>> 15/09/07 13:45:22 INFO SecurityManager: Changing view acls to: hivedata
>>> 15/09/07 13:45:22 INFO SecurityManager: Changing modify acls to: hivedata
>>> 15/09/07 13:45:22 INFO SecurityManager: SecurityManager: authentication
>>> disabled; ui acls disabled; users with view permissions: Set(hivedata);
>>> users with modify permissions: Set(hivedata)
>>> 15/09/07 13:45:23 INFO HttpServer: Starting HTTP Server
>>> 15/09/07 13:45:23 INFO Utils: Successfully started service 'HTTP class
>>> server' on port 43731.
>>> Welcome to
>>> ____ __
>>> / __/__ ___ _____/ /__
>>> _\ \/ _ \/ _ `/ __/ '_/
>>> /___/ .__/\_,_/_/ /_/\_\ version 1.4.1
>>> /_/
>>>
>>> Using Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java
>>> 1.8.0)
>>> Type in expressions to have them evaluated.
>>> Type :help for more information.
>>> 15/09/07 13:45:26 INFO SparkContext: Running Spark version 1.4.1
>>> 15/09/07 13:45:26 INFO SecurityManager: Changing view acls to: hivedata
>>> 15/09/07 13:45:26 INFO SecurityManager: Changing modify acls to: hivedata
>>> 15/09/07 13:45:26 INFO SecurityManager: SecurityManager: authentication
>>> disabled; ui acls disabled; users with view permissions: Set(hivedata);
>>> users with modify permissions: Set(hivedata)
>>> 15/09/07 13:45:27 INFO Slf4jLogger: Slf4jLogger started
>>> 15/09/07 13:45:27 INFO Remoting: Starting remoting
>>> 15/09/07 13:45:27 INFO Remoting: Remoting started; listening on
>>> addresses :[akka.tcp://sparkDriver@10.10.30.52:46083]
>>> 15/09/07 13:45:27 INFO Utils: Successfully started service 'sparkDriver'
>>> on port 46083.
>>> 15/09/07 13:45:27 INFO SparkEnv: Registering MapOutputTracker
>>> 15/09/07 13:45:27 INFO SparkEnv: Registering BlockManagerMaster
>>> 15/09/07 13:45:27 INFO DiskBlockManager: Created local directory at
>>> /tmp/spark-f313315a-0769-4057-835d-196cfe140a26/blockmgr-bd1b8498-9f6a-47c4-ae59-8800563f97d0
>>> 15/09/07 13:45:27 INFO MemoryStore: MemoryStore started with capacity
>>> 265.1 MB
>>> 15/09/07 13:45:27 INFO HttpFileServer: HTTP File server directory is
>>> /tmp/spark-f313315a-0769-4057-835d-196cfe140a26/httpd-3fbe0c9d-c0c5-41ef-bf72-4f0ef59bfa21
>>> 15/09/07 13:45:27 INFO HttpServer: Starting HTTP Server
>>> 15/09/07 13:45:27 INFO Utils: Successfully started service 'HTTP file
>>> server' on port 38717.
>>> 15/09/07 13:45:27 INFO SparkEnv: Registering OutputCommitCoordinator
>>> 15/09/07 13:45:27 WARN Utils: Service 'SparkUI' could not bind on port
>>> 4040. Attempting port 4041.
>>> 15/09/07 13:45:27 INFO Utils: Successfully started service 'SparkUI' on
>>> port 4041.
>>> 15/09/07 13:45:27 INFO SparkUI: Started SparkUI at
>>> http://10.10.30.52:4041
>>> 15/09/07 13:45:27 INFO Executor: Starting executor ID driver on host
>>> localhost
>>> 15/09/07 13:45:27 INFO Executor: Using REPL class URI:
>>> http://10.10.30.52:43731
>>> 15/09/07 13:45:27 INFO Utils: Successfully started service
>>> 'org.apache.spark.network.netty.NettyBlockTransferService' on port 60973.
>>> 15/09/07 13:45:27 INFO NettyBlockTransferService: Server created on 60973
>>> 15/09/07 13:45:27 INFO BlockManagerMaster: Trying to register
>>> BlockManager
>>> 15/09/07 13:45:27 INFO BlockManagerMasterEndpoint: Registering block
>>> manager localhost:60973 with 265.1 MB RAM, BlockManagerId(driver,
>>> localhost, 60973)
>>> 15/09/07 13:45:27 INFO BlockManagerMaster: Registered BlockManager
>>> 15/09/07 13:45:28 INFO SparkILoop: Created spark context..
>>> Spark context available as sc.
>>> 15/09/07 13:45:28 INFO HiveContext: Initializing execution hive, version
>>> 0.13.1
>>> 15/09/07 13:45:28 INFO HiveMetaStore: 0: Opening raw store with
>>> implemenation class:org.apache.hadoop.hive.metastore.ObjectStore
>>> 15/09/07 13:45:29 INFO ObjectStore: ObjectStore, initialize called
>>> 15/09/07 13:45:29 INFO Persistence: Property
>>> hive.metastore.integral.jdo.pushdown unknown - will be ignored
>>> 15/09/07 13:45:29 INFO Persistence: Property datanucleus.cache.level2
>>> unknown - will be ignored
>>> 15/09/07 13:45:29 WARN Connection: BoneCP specified but not present in
>>> CLASSPATH (or one of dependencies)
>>> 15/09/07 13:45:29 WARN Connection: BoneCP specified but not present in
>>> CLASSPATH (or one of dependencies)
>>> 15/09/07 13:45:36 INFO ObjectStore: Setting MetaStore object pin classes
>>> with
>>> hive.metastore.cache.pinobjtypes="Table,StorageDescriptor,SerDeInfo,Partition,Database,Type,FieldSchema,Order"
>>> 15/09/07 13:45:36 INFO MetaStoreDirectSql: MySQL check failed, assuming
>>> we are not on mysql: Lexical error at line 1, column 5. Encountered: "@"
>>> (64), after : "".
>>> 15/09/07 13:45:37 INFO Datastore: The class
>>> "org.apache.hadoop.hive.metastore.model.MFieldSchema" is tagged as
>>> "embedded-only" so does not have its own datastore table.
>>> 15/09/07 13:45:37 INFO Datastore: The class
>>> "org.apache.hadoop.hive.metastore.model.MOrder" is tagged as
>>> "embedded-only" so does not have its own datastore table.
>>> 15/09/07 13:45:42 INFO Datastore: The class
>>> "org.apache.hadoop.hive.metastore.model.MFieldSchema" is tagged as
>>> "embedded-only" so does not have its own datastore table.
>>> 15/09/07 13:45:42 INFO Datastore: The class
>>> "org.apache.hadoop.hive.metastore.model.MOrder" is tagged as
>>> "embedded-only" so does not have its own datastore table.
>>> 15/09/07 13:45:43 INFO ObjectStore: Initialized ObjectStore
>>> 15/09/07 13:45:43 WARN ObjectStore: Version information not found in
>>> metastore. hive.metastore.schema.verification is not enabled so recording
>>> the schema version 0.13.1aa
>>> 15/09/07 13:45:44 INFO HiveMetaStore: Added admin role in metastore
>>> 15/09/07 13:45:44 INFO HiveMetaStore: Added public role in metastore
>>> 15/09/07 13:45:44 INFO HiveMetaStore: No user is added in admin role,
>>> since config is empty
>>> 15/09/07 13:45:45 INFO SessionState: No Tez session required at this
>>> point. hive.execution.engine=mr.
>>> 15/09/07 13:45:45 INFO SparkILoop: Created sql context (with Hive
>>> support)..
>>> SQL context available as sqlContext.
>>>
>>> scala> val df = sqlContext.parquetFile("stats.parquet").cache
>>> warning: there were 1 deprecation warning(s); re-run with -deprecation
>>> for details
>>> SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
>>> SLF4J: Defaulting to no-operation (NOP) logger implementation
>>> SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for
>>> further details.
>>> 15/09/07 13:45:49 INFO HiveContext: Initializing HiveMetastoreConnection
>>> version 0.13.1 using Spark classes.
>>> 15/09/07 13:45:49 WARN NativeCodeLoader: Unable to load native-hadoop
>>> library for your platform... using builtin-java classes where applicable
>>> 15/09/07 13:45:49 INFO HiveMetaStore: 0: Opening raw store with
>>> implemenation class:org.apache.hadoop.hive.metastore.ObjectStore
>>> 15/09/07 13:45:49 INFO ObjectStore: ObjectStore, initialize called
>>> 15/09/07 13:45:50 INFO Persistence: Property
>>> hive.metastore.integral.jdo.pushdown unknown - will be ignored
>>> 15/09/07 13:45:50 INFO Persistence: Property datanucleus.cache.level2
>>> unknown - will be ignored
>>> 15/09/07 13:45:50 WARN Connection: BoneCP specified but not present in
>>> CLASSPATH (or one of dependencies)
>>> 15/09/07 13:45:50 WARN Connection: BoneCP specified but not present in
>>> CLASSPATH (or one of dependencies)
>>> 15/09/07 13:45:51 INFO ObjectStore: Setting MetaStore object pin classes
>>> with
>>> hive.metastore.cache.pinobjtypes="Table,StorageDescriptor,SerDeInfo,Partition,Database,Type,FieldSchema,Order"
>>> 15/09/07 13:45:51 INFO MetaStoreDirectSql: MySQL check failed, assuming
>>> we are not on mysql: Lexical error at line 1, column 5. Encountered: "@"
>>> (64), after : "".
>>> 15/09/07 13:45:52 INFO Datastore: The class
>>> "org.apache.hadoop.hive.metastore.model.MFieldSchema" is tagged as
>>> "embedded-only" so does not have its own datastore table.
>>> 15/09/07 13:45:52 INFO Datastore: The class
>>> "org.apache.hadoop.hive.metastore.model.MOrder" is tagged as
>>> "embedded-only" so does not have its own datastore table.
>>> 15/09/07 13:45:52 INFO Datastore: The class
>>> "org.apache.hadoop.hive.metastore.model.MFieldSchema" is tagged as
>>> "embedded-only" so does not have its own datastore table.
>>> 15/09/07 13:45:52 INFO Datastore: The class
>>> "org.apache.hadoop.hive.metastore.model.MOrder" is tagged as
>>> "embedded-only" so does not have its own datastore table.
>>> 15/09/07 13:45:52 INFO Query: Reading in results for query
>>> "org.datanucleus.store.rdbms.query.SQLQuery@0" since the connection
>>> used is closing
>>> 15/09/07 13:45:52 INFO ObjectStore: Initialized ObjectStore
>>> 15/09/07 13:45:53 INFO HiveMetaStore: Added admin role in metastore
>>> 15/09/07 13:45:53 INFO HiveMetaStore: Added public role in metastore
>>> 15/09/07 13:45:53 INFO HiveMetaStore: No user is added in admin role,
>>> since config is empty
>>> 15/09/07 13:45:53 INFO SessionState: No Tez session required at this
>>> point. hive.execution.engine=mr.
>>> 15/09/07 13:45:53 INFO MemoryStore: ensureFreeSpace(213456) called with
>>> curMem=0, maxMem=278019440
>>> 15/09/07 13:45:53 INFO MemoryStore: Block broadcast_0 stored as values
>>> in memory (estimated size 208.5 KB, free 264.9 MB)
>>> 15/09/07 13:45:53 INFO MemoryStore: ensureFreeSpace(19750) called with
>>> curMem=213456, maxMem=278019440
>>> 15/09/07 13:45:53 INFO MemoryStore: Block broadcast_0_piece0 stored as
>>> bytes in memory (estimated size 19.3 KB, free 264.9 MB)
>>> 15/09/07 13:45:53 INFO BlockManagerInfo: Added broadcast_0_piece0 in
>>> memory on localhost:60973 (size: 19.3 KB, free: 265.1 MB)
>>> 15/09/07 13:45:53 INFO SparkContext: Created broadcast 0 from cache at
>>> <console>:19
>>> dataFrame: org.apache.spark.sql.DataFrame = [date_time: string, type:
>>> string, type_value: string, newly_observed: string, risk_score: string,
>>> dates_seen: array<string>, hosts_current: array<string>, hosts_historical:
>>> array<string>, md5s_current: array<string>, md5s_historical: array<string>,
>>> processes_current: array<string>, processes_historical: array<string>,
>>> paths_current: array<string>, paths_historical: array<string>,
>>> ports_current: array<string>, ports_historical: array<string>]
>>>
>>> scala> val values = df.first
>>> 15/09/07 13:45:58 INFO deprecation: mapred.max.split.size is deprecated.
>>> Instead, use mapreduce.input.fileinputformat.split.maxsize
>>> 15/09/07 13:45:58 INFO deprecation: mapred.min.split.size is deprecated.
>>> Instead, use mapreduce.input.fileinputformat.split.minsize
>>> 15/09/07 13:45:58 INFO
>>> ParquetRelation2$$anonfun$buildScan$1$$anon$1$$anon$2: Using Task Side
>>> Metadata Split Strategy
>>> 15/09/07 13:45:58 INFO SparkContext: Starting job: first at <console>:21
>>> 15/09/07 13:45:59 INFO DAGScheduler: Got job 0 (first at <console>:21)
>>> with 1 output partitions (allowLocal=false)
>>> 15/09/07 13:45:59 INFO DAGScheduler: Final stage: ResultStage 0(first at
>>> <console>:21)
>>> 15/09/07 13:45:59 INFO DAGScheduler: Parents of final stage: List()
>>> 15/09/07 13:45:59 INFO DAGScheduler: Missing parents: List()
>>> 15/09/07 13:45:59 INFO DAGScheduler: Submitting ResultStage 0
>>> (MapPartitionsRDD[4] at first at <console>:21), which has no missing parents
>>> 15/09/07 13:45:59 INFO MemoryStore: ensureFreeSpace(22552) called with
>>> curMem=233206, maxMem=278019440
>>> 15/09/07 13:45:59 INFO MemoryStore: Block broadcast_1 stored as values
>>> in memory (estimated size 22.0 KB, free 264.9 MB)
>>> 15/09/07 13:45:59 INFO MemoryStore: ensureFreeSpace(8219) called with
>>> curMem=255758, maxMem=278019440
>>> 15/09/07 13:45:59 INFO MemoryStore: Block broadcast_1_piece0 stored as
>>> bytes in memory (estimated size 8.0 KB, free 264.9 MB)
>>> 15/09/07 13:45:59 INFO BlockManagerInfo: Added broadcast_1_piece0 in
>>> memory on localhost:60973 (size: 8.0 KB, free: 265.1 MB)
>>> 15/09/07 13:45:59 INFO SparkContext: Created broadcast 1 from broadcast
>>> at DAGScheduler.scala:874
>>> 15/09/07 13:45:59 INFO DAGScheduler: Submitting 1 missing tasks from
>>> ResultStage 0 (MapPartitionsRDD[4] at first at <console>:21)
>>> 15/09/07 13:45:59 INFO TaskSchedulerImpl: Adding task set 0.0 with 1
>>> tasks
>>> 15/09/07 13:45:59 INFO TaskSetManager: Starting task 0.0 in stage 0.0
>>> (TID 0, localhost, PROCESS_LOCAL, 1894 bytes)
>>> 15/09/07 13:45:59 INFO Executor: Running task 0.0 in stage 0.0 (TID 0)
>>> 15/09/07 13:45:59 INFO CacheManager: Partition rdd_2_0 not found,
>>> computing it
>>> 15/09/07 13:45:59 INFO ParquetRelation2$$anonfun$buildScan$1$$anon$1:
>>> Input split: ParquetInputSplit{part:
>>> file:/home/hivedata/spark-1.4.1-bin-hadoop2.6/stats.parquet start: 0 end:
>>> 2373831 length: 2373831 hosts: [] requestedSchema: message root {
>>> optional binary date_time (UTF8);
>>> optional binary type (UTF8);
>>> optional binary type_value (UTF8);
>>> optional binary newly_observed (UTF8);
>>> optional binary risk_score (UTF8);
>>> optional group dates_seen (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> optional group hosts_current (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> optional group hosts_historical (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> optional group md5s_current (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> optional group md5s_historical (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> optional group processes_current (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> optional group processes_historical (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> optional group paths_current (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> optional group paths_historical (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> optional group ports_current (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> optional group ports_historical (LIST) {
>>> repeated group bag {
>>> optional binary array (UTF8);
>>> }
>>> }
>>> }
>>> readSupportMetadata:
>>> {org.apache.spark.sql.parquet.row.requested_schema={"type":"struct","fields":[{"name":"date_time","type":"string","nullable":true,"metadata":{}},{"name":"type","type":"string","nullable":true,"metadata":{}},{"name":"type_value","type":"string","nullable":true,"metadata":{}},{"name":"newly_observed","type":"string","nullable":true,"metadata":{}},{"name":"risk_score","type":"string","nullable":true,"metadata":{}},{"name":"dates_seen","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"hosts_current","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"hosts_historical","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"md5s_current","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"md5s_historical","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"processes_current","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"processes_historical","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"paths_current","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"paths_historical","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"ports_current","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"ports_historical","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}}]},
>>> org.apache.spark.sql.parquet.row.metadata={"type":"struct","fields":[{"name":"date_time","type":"string","nullable":true,"metadata":{}},{"name":"type","type":"string","nullable":true,"metadata":{}},{"name":"type_value","type":"string","nullable":true,"metadata":{}},{"name":"newly_observed","type":"string","nullable":true,"metadata":{}},{"name":"risk_score","type":"string","nullable":true,"metadata":{}},{"name":"dates_seen","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"hosts_current","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"hosts_historical","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"md5s_current","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"md5s_historical","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"processes_current","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"processes_historical","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"paths_current","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"paths_historical","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"ports_current","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}},{"name":"ports_historical","type":{"type":"array","elementType":"string","containsNull":true},"nullable":true,"metadata":{}}]}}}
>>> 15/09/07 13:45:59 ERROR Executor: Exception in task 0.0 in stage 0.0
>>> (TID 0)
>>> parquet.io.ParquetDecodingException: Can not read value at 0 in block -1
>>> in file file:/home/hivedata/spark-1.4.1-bin-hadoop2.6/stats.parquet
>>> at
>>> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:213)
>>> at
>>> parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:204)
>>> at
>>> org.apache.spark.sql.sources.SqlNewHadoopRDD$$anon$1.hasNext(SqlNewHadoopRDD.scala:163)
>>> at
>>> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
>>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>>> at
>>> org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1.hasNext(InMemoryColumnarTableScan.scala:160)
>>> at
>>> org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:276)
>>> at
>>> org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:171)
>>> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:242)
>>> at
>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>>> at
>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:63)
>>> at org.apache.spark.scheduler.Task.run(Task.scala:70)
>>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
>>> 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:744)
>>> Caused by: java.lang.ArrayIndexOutOfBoundsException: -1
>>> at java.util.ArrayList.elementData(ArrayList.java:403)
>>> at java.util.ArrayList.get(ArrayList.java:416)
>>> at parquet.io.GroupColumnIO.getLast(GroupColumnIO.java:95)
>>> at parquet.io.GroupColumnIO.getLast(GroupColumnIO.java:95)
>>> at parquet.io.GroupColumnIO.getLast(GroupColumnIO.java:95)
>>> at parquet.io.PrimitiveColumnIO.getLast(PrimitiveColumnIO.java:80)
>>> at parquet.io.PrimitiveColumnIO.isLast(PrimitiveColumnIO.java:74)
>>> at
>>> parquet.io.RecordReaderImplementation.<init>(RecordReaderImplementation.java:290)
>>> at parquet.io.MessageColumnIO$1.visit(MessageColumnIO.java:131)
>>> at parquet.io.MessageColumnIO$1.visit(MessageColumnIO.java:96)
>>> at
>>> parquet.filter2.compat.FilterCompat$NoOpFilter.accept(FilterCompat.java:136)
>>> at parquet.io.MessageColumnIO.getRecordReader(MessageColumnIO.java:96)
>>> at
>>> parquet.hadoop.InternalParquetRecordReader.checkRead(InternalParquetRecordReader.java:126)
>>> at
>>> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:193)
>>> ... 21 more
>>> 15/09/07 13:45:59 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID
>>> 0, localhost): parquet.io.ParquetDecodingException: Can not read value at 0
>>> in block -1 in file
>>> file:/home/hivedata/spark-1.4.1-bin-hadoop2.6/stats.parquet
>>> at
>>> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:213)
>>> at
>>> parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:204)
>>> at
>>> org.apache.spark.sql.sources.SqlNewHadoopRDD$$anon$1.hasNext(SqlNewHadoopRDD.scala:163)
>>> at
>>> org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
>>> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
>>> at
>>> org.apache.spark.sql.columnar.InMemoryRelation$$anonfun$3$$anon$1.hasNext(InMemoryColumnarTableScan.scala:160)
>>> at
>>> org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:276)
>>> at
>>> org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:171)
>>> at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:242)
>>> at
>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>>> at
>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:63)
>>> at org.apache.spark.scheduler.Task.run(Task.scala:70)
>>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
>>> 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:744)
>>> Caused by: java.lang.ArrayIndexOutOfBoundsException: -1
>>> at java.util.ArrayList.elementData(ArrayList.java:403)
>>> at java.util.ArrayList.get(ArrayList.java:416)
>>> at parquet.io.GroupColumnIO.getLast(GroupColumnIO.java:95)
>>> at parquet.io.GroupColumnIO.getLast(GroupColumnIO.java:95)
>>> at parquet.io.GroupColumnIO.getLast(GroupColumnIO.java:95)
>>> at parquet.io.PrimitiveColumnIO.getLast(PrimitiveColumnIO.java:80)
>>> at parquet.io.PrimitiveColumnIO.isLast(PrimitiveColumnIO.java:74)
>>> at
>>> parquet.io.RecordReaderImplementation.<init>(RecordReaderImplementation.java:290)
>>> at parquet.io.MessageColumnIO$1.visit(MessageColumnIO.java:131)
>>> at parquet.io.MessageColumnIO$1.visit(MessageColumnIO.java:96)
>>> at
>>> parquet.filter2.compat.FilterCompat$NoOpFilter.accept(FilterCompat.java:136)
>>> at parquet.io.MessageColumnIO.getRecordReader(MessageColumnIO.java:96)
>>> at
>>> parquet.hadoop.InternalParquetRecordReader.checkRead(InternalParquetRecordReader.java:126)
>>> at
>>> parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:193)
>>> ... 21 more
>>> {code}
>>>
>>> The file reads fine with parquet-tools. The code has been downloaded
>>> from http://spark.apache.org/downloads.html.
>>>
>>> The code does works with non-array types.
>>>
>>> I would file a bug, but Apache JIRA refuses to register me (actually,
>>> re-register since I lost my previous account).
>>>
>>> --
>>> ale...@gmail.com
>>>
>>
>
>
> --
> Alex Kozlov
> (408) 507-4987
> (408) 830-9982 fax
> (650) 887-2135 efax
> ale...@gmail.com
>
