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Fernando Pereira 13268a58f8 [SPARK-22649][PYTHON][SQL] Adding localCheckpoint to Dataset API 
## What changes were proposed in this pull request?

This change adds local checkpoint support to datasets and respective bind from Python Dataframe API.

If reliability requirements can be lowered to favor performance, as in cases of further quick transformations followed by a reliable save, localCheckpoints() fit very well.
Furthermore, at the moment Reliable checkpoints still incur double computation (see #9428)
In general it makes the API more complete as well.

## How was this patch tested?

Python land quick use case:

```python
>>> from time import sleep
>>> from pyspark.sql import types as T
>>> from pyspark.sql import functions as F

>>> def f(x):
    sleep(1)
    return x*2
   ...:

>>> df1 = spark.range(30, numPartitions=6)
>>> df2 = df1.select(F.udf(f, T.LongType())("id"))

>>> %time _ = df2.collect()
CPU times: user 7.79 ms, sys: 5.84 ms, total: 13.6 ms
Wall time: 12.2 s

>>> %time df3 = df2.localCheckpoint()
CPU times: user 2.38 ms, sys: 2.3 ms, total: 4.68 ms
Wall time: 10.3 s

>>> %time _ = df3.collect()
CPU times: user 5.09 ms, sys: 410 µs, total: 5.5 ms
Wall time: 148 ms

>>> sc.setCheckpointDir(".")
>>> %time df3 = df2.checkpoint()
CPU times: user 4.04 ms, sys: 1.63 ms, total: 5.67 ms
Wall time: 20.3 s
```

Author: Fernando Pereira <fernando.pereira@epfl.ch>

Closes #19805 from ferdonline/feature_dataset_localCheckpoint.
2017-12-19 20:47:12 -08:00
..
catalyst [SPARK-22829] Add new built-in function date_trunc() 2017-12-19 20:22:33 -08:00
core [SPARK-22649][PYTHON][SQL] Adding localCheckpoint to Dataset API 2017-12-19 20:47:12 -08:00
hive [SPARK-22745][SQL] read partition stats from Hive 2017-12-13 16:27:29 +08:00
hive-thriftserver Revert "Revert "[SPARK-22496][SQL] thrift server adds operation logs"" 2017-12-19 07:30:29 +09:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -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.

Running sql/create-docs.sh generates SQL documentation for built-in functions under sql/site.