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Copy file name to clipboardExpand all lines: docs/src/reference/asciidoc/core/intro/requirements.adoc
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@@ -10,7 +10,7 @@ TIP: {eh} adds no extra requirements to Hadoop (or the various libraries built o
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[[requirements-jdk]]
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=== JDK
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JDK level 6.0 (or above) just like Hadoop. As JDK 6 as well as JDK 7 have been both EOL-ed and are not supported by recent product updates, we strongly recommend using the latest JDK 8 (at least u20 or higher). If that is not an option, use JDK 7.0 update u55 (required for Elasticsearch 1.2 or higher). An up-to-date support matrix for Elasticsearch is available https://www.elastic.co/subscriptions/matrix[here]. Do note that the JVM versions are *critical* for a stable environment as an incorrect version can corrupt the data underneath as explained in this http://www.elastic.co/blog/java-1-7u55-safe-use-elasticsearch-lucene/[blog post].
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JDK level 8 (at least u20 or higher). An up-to-date support matrix for Elasticsearch is available https://www.elastic.co/subscriptions/matrix[here]. Do note that the JVM versions are *critical* for a stable environment as an incorrect version can corrupt the data underneath as explained in this http://www.elastic.co/blog/java-1-7u55-safe-use-elasticsearch-lucene/[blog post].
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One can check the available JDK version from the command line:
Hadoop 2.x (ideally the latest stable version, currently 2.7.3). {eh} is tested daily against Apache Hadoop; any distro compatible with Apache Hadoop should work just fine.
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{eh} is compatible with Hadoop 2 and Hadoop 3 (ideally the latest stable version). It is tested daily against Apache Hadoop, but any distro
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compatible with Apache Hadoop should work just fine.
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To check the version of Hadoop, one can refer either to its folder or jars (which contain the version in their names) or from the command line:
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[source, bash]
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----
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$ bin/hadoop version
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Hadoop 2.4.1
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Hadoop 3.3.1
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----
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[[requirements-yarn]]
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=== Apache YARN / Hadoop 2.x
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{eh} binary is tested against Hadoop 2.x and designed to run on Yarn without any changes or modifications.
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[[requirements-hive]]
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=== Apache Hive
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The same applies when using the Hadoop layer to integrate the two as {eh} supports the majority of
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Hadoop distributions out there.
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The Spark version can be typically discovery by looking at its folder name:
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The Spark version can be typically discovered by looking at its folder name:
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["source","bash",subs="attributes"]
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[[requirements-spark-sql]]
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==== Apache Spark SQL
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If planning on using Spark SQL make sure to download the appropriate jar. While it is part of the Spark distribution,
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it is _not_ part of Spark core but rather has its own jar. Thus, when constructing the classpath make sure to
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If planning on using Spark SQL make sure to add the appropriate Spark SQL jar as a dependency. While it is part of the Spark distribution,
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it is _not_ part of the Spark core jar but rather has its own jar. Thus, when constructing the classpath make sure to
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include +spark-sql-<scala-version>.jar+ or the Spark _assembly_ : +spark-assembly-{sp-v}-<distro>.jar+
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{eh} supports Spark SQL 1.3 though 1.6 and also Spark SQL 2.0. Since Spark 2.x is not compatible with Spark 1.x,
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two different artifacts are provided by {eh}.
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{eh} supports Spark SQL {sp-v} through its main jar. Since Spark SQL 2.0 is _not_
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