spark-instrumented-optimizer/sql/core/pom.xml
Bryan Cutler d03aebbe65 [SPARK-13534][PYSPARK] Using Apache Arrow to increase performance of DataFrame.toPandas
## What changes were proposed in this pull request?
Integrate Apache Arrow with Spark to increase performance of `DataFrame.toPandas`.  This has been done by using Arrow to convert data partitions on the executor JVM to Arrow payload byte arrays where they are then served to the Python process.  The Python DataFrame can then collect the Arrow payloads where they are combined and converted to a Pandas DataFrame.  Data types except complex, date, timestamp, and decimal  are currently supported, otherwise an `UnsupportedOperation` exception is thrown.

Additions to Spark include a Scala package private method `Dataset.toArrowPayload` that will convert data partitions in the executor JVM to `ArrowPayload`s as byte arrays so they can be easily served.  A package private class/object `ArrowConverters` that provide data type mappings and conversion routines.  In Python, a private method `DataFrame._collectAsArrow` is added to collect Arrow payloads and a SQLConf "spark.sql.execution.arrow.enable" can be used in `toPandas()` to enable using Arrow (uses the old conversion by default).

## How was this patch tested?
Added a new test suite `ArrowConvertersSuite` that will run tests on conversion of Datasets to Arrow payloads for supported types.  The suite will generate a Dataset and matching Arrow JSON data, then the dataset is converted to an Arrow payload and finally validated against the JSON data.  This will ensure that the schema and data has been converted correctly.

Added PySpark tests to verify the `toPandas` method is producing equal DataFrames with and without pyarrow.  A roundtrip test to ensure the pandas DataFrame produced by pyspark is equal to a one made directly with pandas.

Author: Bryan Cutler <cutlerb@gmail.com>
Author: Li Jin <ice.xelloss@gmail.com>
Author: Li Jin <li.jin@twosigma.com>
Author: Wes McKinney <wes.mckinney@twosigma.com>

Closes #18459 from BryanCutler/toPandas_with_arrow-SPARK-13534.
2017-07-10 15:21:03 -07:00

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XML

<?xml version="1.0" encoding="UTF-8"?>
<!--
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~ The ASF licenses this file to You under the Apache License, Version 2.0
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~ distributed under the License is distributed on an "AS IS" BASIS,
~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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~ limitations under the License.
-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.apache.spark</groupId>
<artifactId>spark-parent_2.11</artifactId>
<version>2.3.0-SNAPSHOT</version>
<relativePath>../../pom.xml</relativePath>
</parent>
<artifactId>spark-sql_2.11</artifactId>
<packaging>jar</packaging>
<name>Spark Project SQL</name>
<url>http://spark.apache.org/</url>
<properties>
<sbt.project.name>sql</sbt.project.name>
</properties>
<dependencies>
<dependency>
<groupId>com.univocity</groupId>
<artifactId>univocity-parsers</artifactId>
<version>2.2.1</version>
<type>jar</type>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sketch_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_${scala.binary.version}</artifactId>
<version>${project.version}</version>
<type>test-jar</type>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-catalyst_${scala.binary.version}</artifactId>
<version>${project.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-catalyst_${scala.binary.version}</artifactId>
<version>${project.version}</version>
<type>test-jar</type>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-tags_${scala.binary.version}</artifactId>
</dependency>
<!--
This spark-tags test-dep is needed even though it isn't used in this module, otherwise testing-cmds that exclude
them will yield errors.
-->
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-tags_${scala.binary.version}</artifactId>
<type>test-jar</type>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.parquet</groupId>
<artifactId>parquet-column</artifactId>
</dependency>
<dependency>
<groupId>org.apache.parquet</groupId>
<artifactId>parquet-hadoop</artifactId>
</dependency>
<dependency>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-servlet</artifactId>
</dependency>
<dependency>
<groupId>com.fasterxml.jackson.core</groupId>
<artifactId>jackson-databind</artifactId>
<version>${fasterxml.jackson.version}</version>
</dependency>
<dependency>
<groupId>org.apache.arrow</groupId>
<artifactId>arrow-vector</artifactId>
</dependency>
<dependency>
<groupId>org.apache.xbean</groupId>
<artifactId>xbean-asm5-shaded</artifactId>
</dependency>
<dependency>
<groupId>org.scalacheck</groupId>
<artifactId>scalacheck_${scala.binary.version}</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>com.h2database</groupId>
<artifactId>h2</artifactId>
<version>1.4.195</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.postgresql</groupId>
<artifactId>postgresql</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.parquet</groupId>
<artifactId>parquet-avro</artifactId>
<scope>test</scope>
</dependency>
<!--
This version of avro test-dep is different from the one defined
in the parent pom. The parent pom has avro 1.7.7 test-dep for Hadoop.
Here, ParquetAvroCompatibilitySuite uses parquet-avro's AvroParquetWriter
which uses avro 1.8.0+ specific API. In Maven 3, we need to have
this here to have different versions for the same artifact.
-->
<dependency>
<groupId>org.apache.avro</groupId>
<artifactId>avro</artifactId>
<version>1.8.1</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.mockito</groupId>
<artifactId>mockito-core</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<build>
<outputDirectory>target/scala-${scala.binary.version}/classes</outputDirectory>
<testOutputDirectory>target/scala-${scala.binary.version}/test-classes</testOutputDirectory>
<plugins>
<!--
This plugin forces the generation of jar containing sql test classes,
so that the tests classes of external modules can use them. The two execution profiles
are necessary - first one for 'mvn package', second one for 'mvn test-compile'. Ideally,
'mvn compile' should not compile test classes and therefore should not need this.
However, a closed due to "Cannot Reproduce" Maven bug (https://issues.apache.org/jira/browse/MNG-3559)
causes the compilation to fail if catalyst test-jar is not generated. Hence, the
second execution profile for 'mvn test-compile'.
-->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-jar-plugin</artifactId>
<executions>
<execution>
<goals>
<goal>test-jar</goal>
</goals>
</execution>
<execution>
<id>test-jar-on-test-compile</id>
<phase>test-compile</phase>
<goals>
<goal>test-jar</goal>
</goals>
</execution>
</executions>
</plugin>
<plugin>
<groupId>org.scalatest</groupId>
<artifactId>scalatest-maven-plugin</artifactId>
<configuration>
<argLine>-Xmx4g -Xss4096k -XX:MaxPermSize=${MaxPermGen} -XX:ReservedCodeCacheSize=512m</argLine>
</configuration>
</plugin>
<plugin>
<groupId>org.codehaus.mojo</groupId>
<artifactId>build-helper-maven-plugin</artifactId>
<executions>
<execution>
<id>add-scala-test-sources</id>
<phase>generate-test-sources</phase>
<goals>
<goal>add-test-source</goal>
</goals>
<configuration>
<sources>
<source>src/test/gen-java</source>
</sources>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>