Welcome to Spark Python API Docs!

Contents:

• pyspark package
  • Subpackages
  • Contents
• pyspark.sql module
  • Module Context
  • pyspark.sql.types module
  • pyspark.sql.functions module
• pyspark.streaming module
  • Module contents
  • pyspark.streaming.kafka module
  • pyspark.streaming.kinesis module
  • pyspark.streaming.flume.module
  • pyspark.streaming.mqtt module
• pyspark.ml package
  • ML Pipeline APIs
  • pyspark.ml.param module
  • pyspark.ml.feature module
  • pyspark.ml.classification module
  • pyspark.ml.clustering module
  • pyspark.ml.recommendation module
  • pyspark.ml.regression module
  • pyspark.ml.tuning module
  • pyspark.ml.evaluation module
• pyspark.mllib package
  • pyspark.mllib.classification module
  • pyspark.mllib.clustering module
  • pyspark.mllib.evaluation module
  • pyspark.mllib.feature module
  • pyspark.mllib.fpm module
  • pyspark.mllib.linalg module
  • pyspark.mllib.linalg.distributed module
  • pyspark.mllib.random module
  • pyspark.mllib.recommendation module
  • pyspark.mllib.regression module
  • pyspark.mllib.stat module
  • pyspark.mllib.tree module
  • pyspark.mllib.util module

Core classes:

pyspark.SparkContext

Main entry point for Spark functionality.

pyspark.RDD

A Resilient Distributed Dataset (RDD), the basic abstraction in Spark.

pyspark.streaming.StreamingContext

Main entry point for Spark Streaming functionality.

pyspark.streaming.DStream

A Discretized Stream (DStream), the basic abstraction in Spark Streaming.

pyspark.sql.SQLContext

Main entry point for DataFrame and SQL functionality.

pyspark.sql.DataFrame

A distributed collection of data grouped into named columns.

Indices and tables

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