spark-instrumented-optimizer/python/pyspark/__init__.py

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# The ASF licenses this file to You under the Apache License, Version 2.0
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#    http://www.apache.org/licenses/LICENSE-2.0
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"""
PySpark is the Python API for Spark.

Public classes:

  - L{SparkContext<pyspark.context.SparkContext>}
      Main entry point for Spark functionality.
  - L{RDD<pyspark.rdd.RDD>}
      A Resilient Distributed Dataset (RDD), the basic abstraction in Spark.
  - L{Broadcast<pyspark.broadcast.Broadcast>}
      A broadcast variable that gets reused across tasks.
  - L{Accumulator<pyspark.accumulators.Accumulator>}
      An "add-only" shared variable that tasks can only add values to.
  - L{SparkConf<pyspark.conf.SparkConf>}
      For configuring Spark.
  - L{SparkFiles<pyspark.files.SparkFiles>}
      Access files shipped with jobs.
  - L{StorageLevel<pyspark.storagelevel.StorageLevel>}
      Finer-grained cache persistence levels.

Spark SQL:
  - L{SQLContext<pyspark.sql.SQLContext>}
      Main entry point for SQL functionality.
  - L{SchemaRDD<pyspark.sql.SchemaRDD>}
      A Resilient Distributed Dataset (RDD) with Schema information for the data contained. In
      addition to normal RDD operations, SchemaRDDs also support SQL.
  - L{Row<pyspark.sql.Row>}
      A Row of data returned by a Spark SQL query.

Hive:
  - L{HiveContext<pyspark.context.HiveContext>}
      Main entry point for accessing data stored in Apache Hive..
"""

# The following block allows us to import python's random instead of mllib.random for scripts in
# mllib that depend on top level pyspark packages, which transitively depend on python's random.
# Since Python's import logic looks for modules in the current package first, we eliminate
# mllib.random as a candidate for C{import random} by removing the first search path, the script's
# location, in order to force the loader to look in Python's top-level modules for C{random}.
import sys
s = sys.path.pop(0)
import random
sys.path.insert(0, s)

from pyspark.conf import SparkConf
from pyspark.context import SparkContext
from pyspark.sql import SQLContext
from pyspark.rdd import RDD
from pyspark.sql import SchemaRDD
from pyspark.sql import Row
from pyspark.files import SparkFiles
from pyspark.storagelevel import StorageLevel


__all__ = ["SparkConf", "SparkContext", "SQLContext", "RDD", "SchemaRDD",
           "SparkFiles", "StorageLevel", "Row"]