Repository: spark Updated Branches: refs/heads/master 972673aca -> 2e4075e2e
[SPARK-16557][SQL] Remove stale doc in sql/README.md ## What changes were proposed in this pull request? Most of the documentation in https://github.com/apache/spark/blob/master/sql/README.md is stale. It would be useful to keep the list of projects to explain what's going on, and everything else should be removed. ## How was this patch tested? N/A Author: Reynold Xin <r...@databricks.com> Closes #14211 from rxin/SPARK-16557. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/2e4075e2 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/2e4075e2 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/2e4075e2 Branch: refs/heads/master Commit: 2e4075e2ece9574100c79558cab054485e25c2ee Parents: 972673a Author: Reynold Xin <r...@databricks.com> Authored: Thu Jul 14 19:24:42 2016 -0700 Committer: Reynold Xin <r...@databricks.com> Committed: Thu Jul 14 19:24:42 2016 -0700 ---------------------------------------------------------------------- sql/README.md | 75 +----------------------------------------------------- 1 file changed, 1 insertion(+), 74 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/2e4075e2/sql/README.md ---------------------------------------------------------------------- diff --git a/sql/README.md b/sql/README.md index b090398..58e9097 100644 --- a/sql/README.md +++ b/sql/README.md @@ -1,83 +1,10 @@ Spark SQL ========= -This module provides support for executing relational queries expressed in either SQL or a LINQ-like Scala DSL. +This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API. 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 (i.e. a test suite based on `HiveComparisonTest`), -you will need to setup your development environment based on the following instructions. - -If you are working with Hive 0.12.0, you will need to set several environmental variables as follows. - -``` -export HIVE_HOME="<path to>/hive/build/dist" -export HIVE_DEV_HOME="<path to>/hive/" -export HADOOP_HOME="<path to>/hadoop" -``` - -If you are working with Hive 0.13.1, the following steps are needed: - -1. Download Hive's [0.13.1](https://archive.apache.org/dist/hive/hive-0.13.1) and set `HIVE_HOME` with `export HIVE_HOME="<path to hive>"`. Please do not set `HIVE_DEV_HOME` (See [SPARK-4119](https://issues.apache.org/jira/browse/SPARK-4119)). -2. Set `HADOOP_HOME` with `export HADOOP_HOME="<path to hadoop>"` -3. Download all Hive 0.13.1a jars (Hive jars actually used by Spark) from [here](http://mvnrepository.com/artifact/org.spark-project.hive) and replace corresponding original 0.13.1 jars in `$HIVE_HOME/lib`. -4. Download [Kryo 2.21 jar](http://mvnrepository.com/artifact/com.esotericsoftware.kryo/kryo/2.21) (Note: 2.22 jar does not work) and [Javolution 5.5.1 jar](http://mvnrepository.com/artifact/javolution/javolution/5.5.1) to `$HIVE_HOME/lib`. -5. This step is optional. But, when generating golden answer files, if a Hive query fails and you find that Hive tries to talk to HDFS or you find weird runtime NPEs, set the following in your test suite... - -``` -val testTempDir = Utils.createTempDir() -// We have to use kryo to let Hive correctly serialize some plans. -sql("set hive.plan.serialization.format=kryo") -// Explicitly set fs to local fs. -sql(s"set fs.default.name=file://$testTempDir/") -// Ask Hive to run jobs in-process as a single map and reduce task. -sql("set mapred.job.tracker=local") -``` - -Using the console -================= -An interactive scala console can be invoked by running `build/sbt hive/console`. -From here you can execute queries with HiveQl and manipulate DataFrame by using DSL. - -```scala -$ build/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.util._ -import org.apache.spark.sql.execution -import org.apache.spark.sql.functions._ -import org.apache.spark.sql.hive._ -import org.apache.spark.sql.hive.test.TestHive._ -import org.apache.spark.sql.hive.test.TestHive.implicits._ -import org.apache.spark.sql.types._ -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.DataFrame = [key: int, value: string] -``` - -Query results are `DataFrames` and can be operated as such. -``` -scala> query.collect() -res0: 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 `DataFrames` using the query DSL. -``` -scala> query.where(query("key") > 30).select(avg(query("key"))).collect() -res1: Array[org.apache.spark.sql.Row] = Array([274.79025423728814]) -``` --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
