7c89a8f0c8
Given that a lot of users are trying to use hive 0.13 in spark, and the incompatibility between hive-0.12 and hive-0.13 on the API level I want to propose following approach, which has no or minimum impact on existing hive-0.12 support, but be able to jumpstart the development of hive-0.13 and future version support. Approach: Introduce “hive-version” property, and manipulate pom.xml files to support different hive version at compiling time through shim layer, e.g., hive-0.12.0 and hive-0.13.1. More specifically, 1. For each different hive version, there is a very light layer of shim code to handle API differences, sitting in sql/hive/hive-version, e.g., sql/hive/v0.12.0 or sql/hive/v0.13.1 2. Add a new profile hive-default active by default, which picks up all existing configuration and hive-0.12.0 shim (v0.12.0) if no hive.version is specified. 3. If user specifies different version (currently only 0.13.1 by -Dhive.version = 0.13.1), hive-versions profile will be activated, which pick up hive-version specific shim layer and configuration, mainly the hive jars and hive-version shim, e.g., v0.13.1. 4. With this approach, nothing is changed with current hive-0.12 support. No change by default: sbt/sbt -Phive For example: sbt/sbt -Phive -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 assembly To enable hive-0.13: sbt/sbt -Dhive.version=0.13.1 For example: sbt/sbt -Dhive.version=0.13.1 -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 assembly Note that in hive-0.13, hive-thriftserver is not enabled, which should be fixed by other Jira, and we don’t need -Phive with -Dhive.version in building (probably we should use -Phive -Dhive.version=xxx instead after thrift server is also supported in hive-0.13.1). Author: Zhan Zhang <zhazhan@gmail.com> Author: zhzhan <zhazhan@gmail.com> Author: Patrick Wendell <pwendell@gmail.com> Closes #2241 from zhzhan/spark-2706 and squashes the following commits: 3ece905 [Zhan Zhang] minor fix 410b668 [Zhan Zhang] solve review comments cbb4691 [Zhan Zhang] change run-test for new options 0d4d2ed [Zhan Zhang] rebase 497b0f4 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 8fad1cf [Zhan Zhang] change the pom file and make hive-0.13.1 as the default ab028d1 [Zhan Zhang] rebase 4a2e36d [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 4cb1b93 [zhzhan] Merge pull request #1 from pwendell/pr-2241 b0478c0 [Patrick Wendell] Changes to simplify the build of SPARK-2706 2b50502 [Zhan Zhang] rebase a72c0d4 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark cb22863 [Zhan Zhang] correct the typo 20f6cf7 [Zhan Zhang] solve compatability issue f7912a9 [Zhan Zhang] rebase and solve review feedback 301eb4a [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 10c3565 [Zhan Zhang] address review comments 6bc9204 [Zhan Zhang] rebase and remove temparory repo d3aa3f2 [Zhan Zhang] Merge branch 'master' into spark-2706 cedcc6f [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 3ced0d7 [Zhan Zhang] rebase d9b981d [Zhan Zhang] rebase and fix error due to rollback adf4924 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 3dd50e8 [Zhan Zhang] solve conflicts and remove unnecessary implicts d10bf00 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark dc7bdb3 [Zhan Zhang] solve conflicts 7e0cc36 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark d7c3e1e [Zhan Zhang] Merge branch 'master' into spark-2706 68deb11 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark d48bd18 [Zhan Zhang] address review comments 3ee3b2b [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 57ea52e [Zhan Zhang] Merge branch 'master' into spark-2706 2b0d513 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 9412d24 [Zhan Zhang] address review comments f4af934 [Zhan Zhang] rebase 1ccd7cc [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 128b60b [Zhan Zhang] ignore 0.12.0 test cases for the time being af9feb9 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 5f5619f [Zhan Zhang] restructure the directory and different hive version support 05d3683 [Zhan Zhang] solve conflicts e4c1982 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark 94b4fdc [Zhan Zhang] Spark-2706: hive-0.13.1 support on spark 87ebf3b [Zhan Zhang] Merge branch 'master' into spark-2706 921e914 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark f896b2a [Zhan Zhang] Merge branch 'master' into spark-2706 789ea21 [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark cb53a2c [Zhan Zhang] Merge branch 'master' of https://github.com/apache/spark f6a8a40 [Zhan Zhang] revert ba14f28 [Zhan Zhang] test dbedff3 [Zhan Zhang] Merge remote-tracking branch 'upstream/master' 70964fe [Zhan Zhang] revert fe0f379 [Zhan Zhang] Merge branch 'master' of https://github.com/zhzhan/spark 70ffd93 [Zhan Zhang] revert 42585ec [Zhan Zhang] test 7d5fce2 [Zhan Zhang] test |
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catalyst | ||
core | ||
hive | ||
hive-thriftserver | ||
README.md |
Spark SQL
This module provides support for executing relational queries expressed in either SQL or a LINQ-like Scala DSL.
Spark SQL is broken up into four subprojects:
- Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
- Execution (sql/core) - A query planner / execution engine for translating Catalyst’s logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
- Hive Support (sql/hive) - Includes an extension of SQLContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allows users to run queries that include Hive UDFs, UDAFs, and UDTFs.
- HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.
Other dependencies for developers
In order to create new hive test cases , you will need to set several environmental variables.
export HIVE_HOME="<path to>/hive/build/dist"
export HIVE_DEV_HOME="<path to>/hive/"
export HADOOP_HOME="<path to>/hadoop-1.0.4"
Using the console
An interactive scala console can be invoked by running sbt/sbt hive/console
. From here you can execute queries and inspect the various stages of query optimization.
catalyst$ sbt/sbt hive/console
[info] Starting scala interpreter...
import org.apache.spark.sql.catalyst.analysis._
import org.apache.spark.sql.catalyst.dsl._
import org.apache.spark.sql.catalyst.errors._
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.rules._
import org.apache.spark.sql.catalyst.types._
import org.apache.spark.sql.catalyst.util._
import org.apache.spark.sql.execution
import org.apache.spark.sql.hive._
import org.apache.spark.sql.hive.TestHive._
Welcome to Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_45).
Type in expressions to have them evaluated.
Type :help for more information.
scala> val query = sql("SELECT * FROM (SELECT * FROM src) a")
query: org.apache.spark.sql.SchemaRDD =
== Query Plan ==
== Physical Plan ==
HiveTableScan [key#10,value#11], (MetastoreRelation default, src, None), None
Query results are RDDs and can be operated as such.
scala> query.collect()
res2: Array[org.apache.spark.sql.Row] = Array([238,val_238], [86,val_86], [311,val_311], [27,val_27]...
You can also build further queries on top of these RDDs using the query DSL.
scala> query.where('key === 100).collect()
res3: Array[org.apache.spark.sql.Row] = Array([100,val_100], [100,val_100])
From the console you can even write rules that transform query plans. For example, the above query has redundant project operators that aren't doing anything. This redundancy can be eliminated using the transform
function that is available on all TreeNode
objects.
scala> query.queryExecution.analyzed
res4: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan =
Project [key#10,value#11]
Project [key#10,value#11]
MetastoreRelation default, src, None
scala> query.queryExecution.analyzed transform {
| case Project(projectList, child) if projectList == child.output => child
| }
res5: res17: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan =
Project [key#10,value#11]
MetastoreRelation default, src, None