HBASE-15184 SparkSQL Scan operation doesn't work on kerberos cluster (Ted Malaska)
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tedyu
parent
f47dba74d4
commit
00248656ee
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@ -164,7 +164,7 @@ case class HBaseRelation (val tableName:String,
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HBaseSparkConf.BULKGET_SIZE, HBaseSparkConf.defaultBulkGetSize))
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//create or get latest HBaseContext
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@transient val hbaseContext:HBaseContext = if (useHBaseContext) {
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val hbaseContext:HBaseContext = if (useHBaseContext) {
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LatestHBaseContextCache.latest
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} else {
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val config = HBaseConfiguration.create()
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@ -270,7 +270,7 @@ case class HBaseRelation (val tableName:String,
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} else {
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None
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}
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val hRdd = new HBaseTableScanRDD(this, pushDownFilterJava, requiredQualifierDefinitionList.seq)
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val hRdd = new HBaseTableScanRDD(this, hbaseContext, pushDownFilterJava, requiredQualifierDefinitionList.seq)
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pushDownRowKeyFilter.points.foreach(hRdd.addPoint(_))
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pushDownRowKeyFilter.ranges.foreach(hRdd.addRange(_))
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var resultRDD: RDD[Row] = {
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@ -29,6 +29,7 @@ import org.apache.hadoop.hbase.io.encoding.DataBlockEncoding
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import org.apache.hadoop.hbase.io.hfile.{CacheConfig, HFileContextBuilder, HFileWriterImpl}
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import org.apache.hadoop.hbase.regionserver.{HStore, StoreFile, BloomType}
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import org.apache.hadoop.hbase.util.Bytes
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import org.apache.hadoop.mapred.JobConf
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import org.apache.spark.broadcast.Broadcast
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import org.apache.spark.deploy.SparkHadoopUtil
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import org.apache.spark.rdd.RDD
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@ -228,7 +229,7 @@ class HBaseContext(@transient sc: SparkContext,
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}))
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}
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def applyCreds[T] (configBroadcast: Broadcast[SerializableWritable[Configuration]]){
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def applyCreds[T] (){
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credentials = SparkHadoopUtil.get.getCurrentUserCredentials()
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logDebug("appliedCredentials:" + appliedCredentials + ",credentials:" + credentials)
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@ -440,10 +441,14 @@ class HBaseContext(@transient sc: SparkContext,
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TableMapReduceUtil.initTableMapperJob(tableName, scan,
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classOf[IdentityTableMapper], null, null, job)
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sc.newAPIHadoopRDD(job.getConfiguration,
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val jconf = new JobConf(job.getConfiguration)
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SparkHadoopUtil.get.addCredentials(jconf)
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new NewHBaseRDD(sc,
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classOf[TableInputFormat],
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classOf[ImmutableBytesWritable],
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classOf[Result]).map(f)
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classOf[Result],
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job.getConfiguration,
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this).map(f)
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}
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/**
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@ -474,7 +479,7 @@ class HBaseContext(@transient sc: SparkContext,
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val config = getConf(configBroadcast)
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applyCreds(configBroadcast)
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applyCreds
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// specify that this is a proxy user
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val connection = ConnectionFactory.createConnection(config)
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f(it, connection)
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@ -514,7 +519,7 @@ class HBaseContext(@transient sc: SparkContext,
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Iterator[U]): Iterator[U] = {
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val config = getConf(configBroadcast)
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applyCreds(configBroadcast)
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applyCreds
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val connection = ConnectionFactory.createConnection(config)
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val res = mp(it, connection)
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@ -0,0 +1,36 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.hadoop.hbase.spark
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import org.apache.hadoop.conf.Configuration
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import org.apache.hadoop.mapreduce.InputFormat
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import org.apache.spark.rdd.NewHadoopRDD
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import org.apache.spark.{InterruptibleIterator, Partition, SparkContext, TaskContext}
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class NewHBaseRDD[K,V](@transient sc : SparkContext,
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@transient inputFormatClass: Class[_ <: InputFormat[K, V]],
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@transient keyClass: Class[K],
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@transient valueClass: Class[V],
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@transient conf: Configuration,
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val hBaseContext: HBaseContext) extends NewHadoopRDD(sc,inputFormatClass, keyClass, valueClass, conf) {
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override def compute(theSplit: Partition, context: TaskContext): InterruptibleIterator[(K, V)] = {
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hBaseContext.applyCreds()
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super.compute(theSplit, context)
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}
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}
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@ -20,7 +20,7 @@ package org.apache.hadoop.hbase.spark.datasources
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import java.util.ArrayList
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import org.apache.hadoop.hbase.client._
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import org.apache.hadoop.hbase.spark.{ScanRange, SchemaQualifierDefinition, HBaseRelation, SparkSQLPushDownFilter}
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import org.apache.hadoop.hbase.spark._
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import org.apache.hadoop.hbase.spark.hbase._
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import org.apache.hadoop.hbase.spark.datasources.HBaseResources._
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import org.apache.spark.{SparkEnv, TaskContext, Logging, Partition}
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@ -28,8 +28,8 @@ import org.apache.spark.rdd.RDD
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import scala.collection.mutable
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class HBaseTableScanRDD(relation: HBaseRelation,
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val hbaseContext: HBaseContext,
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@transient val filter: Option[SparkSQLPushDownFilter] = None,
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val columns: Seq[SchemaQualifierDefinition] = Seq.empty
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)extends RDD[Result](relation.sqlContext.sparkContext, Nil) with Logging {
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@ -98,7 +98,8 @@ class HBaseTableScanRDD(relation: HBaseRelation,
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tbr: TableResource,
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g: Seq[Array[Byte]],
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filter: Option[SparkSQLPushDownFilter],
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columns: Seq[SchemaQualifierDefinition]): Iterator[Result] = {
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columns: Seq[SchemaQualifierDefinition],
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hbaseContext: HBaseContext): Iterator[Result] = {
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g.grouped(relation.bulkGetSize).flatMap{ x =>
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val gets = new ArrayList[Get]()
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x.foreach{ y =>
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@ -111,6 +112,7 @@ class HBaseTableScanRDD(relation: HBaseRelation,
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filter.foreach(g.setFilter(_))
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gets.add(g)
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}
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hbaseContext.applyCreds()
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val tmp = tbr.get(gets)
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rddResources.addResource(tmp)
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toResultIterator(tmp)
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@ -208,11 +210,12 @@ class HBaseTableScanRDD(relation: HBaseRelation,
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if (points.isEmpty) {
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Iterator.empty: Iterator[Result]
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} else {
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buildGets(tableResource, points, filter, columns)
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buildGets(tableResource, points, filter, columns, hbaseContext)
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}
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}
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val rIts = scans.par
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.map { scan =>
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hbaseContext.applyCreds()
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val scanner = tableResource.getScanner(scan)
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rddResources.addResource(scanner)
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scanner
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