[SPARK-29376][SQL][PYTHON] Upgrade Apache Arrow to version 0.15.1

Upgrade Apache Arrow to version 0.15.1. This includes Java artifacts and increases the minimum required version of PyArrow also.

Version 0.12.0 to 0.15.1 includes the following selected fixes/improvements relevant to Spark users:

* ARROW-6898 - [Java] Fix potential memory leak in ArrowWriter and several test classes
* ARROW-6874 - [Python] Memory leak in Table.to_pandas() when conversion to object dtype
* ARROW-5579 - [Java] shade flatbuffer dependency
* ARROW-5843 - [Java] Improve the readability and performance of BitVectorHelper#getNullCount
* ARROW-5881 - [Java] Provide functionalities to efficiently determine if a validity buffer has completely 1 bits/0 bits
* ARROW-5893 - [C++] Remove arrow::Column class from C++ library
* ARROW-5970 - [Java] Provide pointer to Arrow buffer
* ARROW-6070 - [Java] Avoid creating new schema before IPC sending
* ARROW-6279 - [Python] Add Table.slice method or allow slices in \_\_getitem\_\_
* ARROW-6313 - [Format] Tracking for ensuring flatbuffer serialized values are aligned in stream/files.
* ARROW-6557 - [Python] Always return pandas.Series from Array/ChunkedArray.to_pandas, propagate field names to Series from RecordBatch, Table
* ARROW-2015 - [Java] Use Java Time and Date APIs instead of JodaTime
* ARROW-1261 - [Java] Add container type for Map logical type
* ARROW-1207 - [C++] Implement Map logical type

Changelog can be seen at https://arrow.apache.org/release/0.15.0.html

Upgrade to get bug fixes, improvements, and maintain compatibility with future versions of PyArrow.

No

Existing tests, manually tested with Python 3.7, 3.8

Closes apache#26133 from BryanCutler/arrow-upgrade-015-SPARK-29376.

Authored-by: Bryan Cutler <[email protected]>
Signed-off-by: HyukjinKwon <[email protected]>

Author: BryanCutler

dev/deps/spark-deps-hadoop-palantir

@@ -10,9 +10,9 @@ apacheds-kerberos-codec-2.0.0-M15.jar
 api-asn1-api-1.0.0-M20.jar
 api-util-1.0.0-M20.jar
 arpack_combined_all-0.1.jar
-arrow-format-0.12.0.jar
-arrow-memory-0.12.0.jar
-arrow-vector-0.12.0.jar
+arrow-format-0.15.1.jar
+arrow-memory-0.15.1.jar
+arrow-vector-0.15.1.jar
 audience-annotations-0.7.0.jar
 automaton-1.11-8.jar
 avro-1.8.2.jar
@@ -87,7 +87,6 @@ hibernate-validator-5.2.4.Final.jar
 hk2-api-2.5.0-b32.jar
 hk2-locator-2.5.0-b32.jar
 hk2-utils-2.5.0-b32.jar
-hppc-0.7.2.jar
 htrace-core4-4.1.0-incubating.jar
 httpclient-4.5.6.jar
 httpcore-4.4.10.jar

pom.xml

@@ -219,9 +219,9 @@
     <commons-crypto.version>1.0.0</commons-crypto.version>
     <!--
     If you are changing Arrow version specification, please check ./python/pyspark/sql/utils.py,
-    ./python/run-tests.py and ./python/setup.py too.
+    and ./python/setup.py too.
     -->
-    <arrow.version>0.12.0</arrow.version>
+    <arrow.version>0.15.1</arrow.version>
 
     <!-- Async shuffle upload plugin dependency versions -->
     <safe-logging.version>1.13.0</safe-logging.version>

python/pyspark/sql/utils.py

@@ -136,9 +136,10 @@ def require_minimum_pyarrow_version():
     """ Raise ImportError if minimum version of pyarrow is not installed
     """
     # TODO(HyukjinKwon): Relocate and deduplicate the version specification.
-    minimum_pyarrow_version = "0.12.1"
+    minimum_pyarrow_version = "0.15.1"
 
     from distutils.version import LooseVersion
+    import os
     try:
         import pyarrow
         have_arrow = True
@@ -150,6 +151,9 @@ def require_minimum_pyarrow_version():
     if LooseVersion(pyarrow.__version__) < LooseVersion(minimum_pyarrow_version):
         raise ImportError("PyArrow >= %s must be installed; however, "
                           "your version was %s." % (minimum_pyarrow_version, pyarrow.__version__))
+    if os.environ.get("ARROW_PRE_0_15_IPC_FORMAT", "0") == "1":
+        raise RuntimeError("Arrow legacy IPC format is not supported in PySpark, "
+                           "please unset ARROW_PRE_0_15_IPC_FORMAT")
 
 
 def require_test_compiled():

python/setup.py

@@ -104,7 +104,7 @@ def _supports_symlinks():
 # For Arrow, you should also check ./pom.xml and ensure there are no breaking changes in the
 # binary format protocol with the Java version, see ARROW_HOME/format/* for specifications.
 _minimum_pandas_version = "0.19.2"
-_minimum_pyarrow_version = "0.12.1"
+_minimum_pyarrow_version = "0.15.1"
 
 try:
     # We copy the shell script to be under pyspark/python/pyspark so that the launcher scripts

sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowConverters.scala

@@ -26,7 +26,7 @@ import org.apache.arrow.flatbuf.MessageHeader
 import org.apache.arrow.memory.BufferAllocator
 import org.apache.arrow.vector._
 import org.apache.arrow.vector.ipc.{ArrowStreamWriter, ReadChannel, WriteChannel}
-import org.apache.arrow.vector.ipc.message.{ArrowRecordBatch, MessageSerializer}
+import org.apache.arrow.vector.ipc.message.{ArrowRecordBatch, IpcOption, MessageSerializer}
 
 import org.apache.spark.TaskContext
 import org.apache.spark.api.java.JavaRDD
@@ -63,7 +63,7 @@ private[sql] class ArrowBatchStreamWriter(
    * End the Arrow stream, does not close output stream.
    */
   def end(): Unit = {
-    ArrowStreamWriter.writeEndOfStream(writeChannel)
+    ArrowStreamWriter.writeEndOfStream(writeChannel, new IpcOption)
   }
 }
 
@@ -250,8 +250,8 @@ private[sql] object ArrowConverters {
         // Only care about RecordBatch messages, skip Schema and unsupported Dictionary messages
         if (msgMetadata.getMessage.headerType() == MessageHeader.RecordBatch) {
 
-          // Buffer backed output large enough to hold the complete serialized message
-          val bbout = new ByteBufferOutputStream(4 + msgMetadata.getMessageLength + bodyLength)
+          // Buffer backed output large enough to hold 8-byte length + complete serialized message
+          val bbout = new ByteBufferOutputStream(8 + msgMetadata.getMessageLength + bodyLength)
 
           // Write message metadata to ByteBuffer output stream
           MessageSerializer.writeMessageBuffer(