
Apache Spark™ - Unified Engine for large-scale data analytics
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.
PySpark Overview — PySpark 4.0.1 documentation - Apache Spark
Spark Connect is a client-server architecture within Apache Spark that enables remote connectivity to Spark clusters from any application. PySpark provides the client for the Spark …
Spark SQL and DataFrames - Spark 4.0.1 Documentation
Spark SQL is a Spark module for structured data processing. Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark with more information about the structure …
Spark Release 3.5.5 - Apache Spark
Dependency changes While being a maintenance release we did still upgrade some dependencies in this release they are: [SPARK-50886]: Upgrade Avro to 1.11.4 You can …
Configuration - Spark 4.0.1 Documentation
Spark provides three locations to configure the system: Spark properties control most application parameters and can be set by using a SparkConf object, or through Java system properties. …
pyspark.sql.DataFrame.where — PySpark 4.0.1 documentation
pyspark.pandas.Series.pandas_on_spark.transform_batch pyspark.pandas.DataFrame.pandas_on_spark.apply_batch …
Structured Streaming Programming Guide - Spark 4.0.1 …
Structured Streaming is a scalable and fault-tolerant stream processing engine built on the Spark SQL engine. You can express your streaming computation the same way you would express a …
Overview - Spark 3.5.6 Documentation
If you’d like to build Spark from source, visit Building Spark. Spark runs on both Windows and UNIX-like systems (e.g. Linux, Mac OS), and it should run on any platform that runs a …
Quickstart: DataFrame — PySpark 4.0.1 documentation - Apache …
DataFrame and Spark SQL share the same execution engine so they can be interchangeably used seamlessly. For example, you can register the DataFrame as a table and run a SQL …
Spark 3.5.5 released - Apache Spark
Spark 3.5.5 released We are happy to announce the availability of Spark 3.5.5! Visit the release notes to read about the new features, or download the release today. Spark News Archive