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Burak Yavuz edeb51a39d [SPARK-17876] Write StructuredStreaming WAL to a stream instead of materializing all at once 
## What changes were proposed in this pull request?

The CompactibleFileStreamLog materializes the whole metadata log in memory as a String. This can cause issues when there are lots of files that are being committed, especially during a compaction batch.
You may come across stacktraces that look like:
```
java.lang.OutOfMemoryError: Requested array size exceeds VM limit
at java.lang.StringCoding.encode(StringCoding.java:350)
at java.lang.String.getBytes(String.java:941)
at org.apache.spark.sql.execution.streaming.FileStreamSinkLog.serialize(FileStreamSinkLog.scala:127)

```
The safer way is to write to an output stream so that we don't have to materialize a huge string.

## How was this patch tested?

Existing unit tests

Author: Burak Yavuz <brkyvz@gmail.com>

Closes #15437 from brkyvz/ser-to-stream.
2016-10-12 21:40:45 -07:00
..
catalyst [SPARK-17884][SQL] To resolve Null pointer exception when casting from empty string to interval type. 2016-10-12 10:14:45 -07:00
core [SPARK-17876] Write StructuredStreaming WAL to a stream instead of materializing all at once 2016-10-12 21:40:45 -07:00
hive [SPARK-17720][SQL] introduce static SQL conf 2016-10-11 20:27:08 -07:00
hive-thriftserver [SPARK-17707][WEBUI] Web UI prevents spark-submit application to be finished 2016-10-07 10:31:41 -07:00
README.md [SPARK-16557][SQL] Remove stale doc in sql/README.md 2016-07-14 19:24:42 -07:00

README.md

Spark SQL

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.