org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.scala Maven / Gradle / Ivy
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.sql.hive.thriftserver
import java.util.{ArrayList => JArrayList, Arrays, List => JList}
import scala.collection.JavaConverters._
import org.apache.commons.lang3.exception.ExceptionUtils
import org.apache.hadoop.hive.metastore.api.{FieldSchema, Schema}
import org.apache.hadoop.hive.ql.Driver
import org.apache.hadoop.hive.ql.processors.CommandProcessorResponse
import org.apache.spark.internal.Logging
import org.apache.spark.sql.{AnalysisException, SQLContext}
import org.apache.spark.sql.execution.{QueryExecution, SQLExecution}
private[hive] class SparkSQLDriver(val context: SQLContext = SparkSQLEnv.sqlContext)
extends Driver
with Logging {
private[hive] var tableSchema: Schema = _
private[hive] var hiveResponse: Seq[String] = _
override def init(): Unit = {
}
private def getResultSetSchema(query: QueryExecution): Schema = {
val analyzed = query.analyzed
logDebug(s"Result Schema: ${analyzed.output}")
if (analyzed.output.isEmpty) {
new Schema(Arrays.asList(new FieldSchema("Response code", "string", "")), null)
} else {
val fieldSchemas = analyzed.output.map { attr =>
new FieldSchema(attr.name, attr.dataType.catalogString, "")
}
new Schema(fieldSchemas.asJava, null)
}
}
override def run(command: String): CommandProcessorResponse = {
// TODO unify the error code
try {
context.sparkContext.setJobDescription(command)
val execution = context.sessionState.executePlan(context.sql(command).logicalPlan)
hiveResponse = SQLExecution.withNewExecutionId(context.sparkSession, execution) {
execution.hiveResultString()
}
tableSchema = getResultSetSchema(execution)
new CommandProcessorResponse(0)
} catch {
case ae: AnalysisException =>
logDebug(s"Failed in [$command]", ae)
new CommandProcessorResponse(1, ExceptionUtils.getStackTrace(ae), null, ae)
case cause: Throwable =>
logError(s"Failed in [$command]", cause)
new CommandProcessorResponse(1, ExceptionUtils.getStackTrace(cause), null, cause)
}
}
override def close(): Int = {
hiveResponse = null
tableSchema = null
0
}
override def getResults(res: JList[_]): Boolean = {
if (hiveResponse == null) {
false
} else {
res.asInstanceOf[JArrayList[String]].addAll(hiveResponse.asJava)
hiveResponse = null
true
}
}
override def getSchema: Schema = tableSchema
override def destroy() {
super.destroy()
hiveResponse = null
tableSchema = null
}
}