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[SPARK-5700] [SQL] [Build] Bumps jets3t to 0.9.3 for hadoop-2.3 and hadoop-2.4 profiles
This is a follow-up PR for #4454 and #4484. JetS3t 0.9.2 contains a log4j.properties file inside the artifact and breaks our tests (see SPARK-5696). This is fixed in 0.9.3. This PR also reverts hotfix changes introduced in #4484. The reason is that asking users to configure HiveThriftServer2 logging configurations in hive-log4j.properties can be unintuitive. <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/4499) <!-- Reviewable:end --> Author: Cheng Lian <[email protected]> Closes #4499 from liancheng/spark-5700 and squashes the following commits: 4f020c7 [Cheng Lian] Bumps jets3t to 0.9.3 for hadoop-2.3 and hadoop-2.4 profiles (cherry picked from commit ba66793) Signed-off-by: Cheng Lian <[email protected]>
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pom.xml

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<properties>
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<hadoop.version>2.3.0</hadoop.version>
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<protobuf.version>2.5.0</protobuf.version>
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<jets3t.version>0.9.2</jets3t.version>
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<jets3t.version>0.9.3</jets3t.version>
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<hbase.version>0.98.7-hadoop2</hbase.version>
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<commons.math3.version>3.1.1</commons.math3.version>
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<avro.mapred.classifier>hadoop2</avro.mapred.classifier>
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<properties>
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<hadoop.version>2.4.0</hadoop.version>
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<protobuf.version>2.5.0</protobuf.version>
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<jets3t.version>0.9.2</jets3t.version>
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<jets3t.version>0.9.3</jets3t.version>
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<hbase.version>0.98.7-hadoop2</hbase.version>
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<commons.math3.version>3.1.1</commons.math3.version>
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<avro.mapred.classifier>hadoop2</avro.mapred.classifier>

sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/HiveThriftServer2.scala

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package org.apache.spark.sql.hive.thriftserver
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import org.apache.commons.logging.LogFactory
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import org.apache.hadoop.hive.common.LogUtils
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import org.apache.hadoop.hive.conf.HiveConf
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import org.apache.hadoop.hive.conf.HiveConf.ConfVars
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import org.apache.hive.service.cli.thrift.{ThriftBinaryCLIService, ThriftHttpCLIService}
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System.exit(-1)
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}
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LogUtils.initHiveLog4j()
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logInfo("Starting SparkContext")
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SparkSQLEnv.init()
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