Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.

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 Connect server, …

“Spark ML” is not an official name but occasionally used to refer to the MLlib DataFrame-based API. This is majorly due to the org.apache.spark.ml Scala package name used by the DataFrame-based …

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. …

Spark supports two types of shared variables: broadcast variables, which can be used to cache a value in memory on all nodes, and accumulators, which are variables that are only “added” to, such as …

Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud, against diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on …

Jul 30, 2009 · There is a SQL config 'spark.sql.parser.escapedStringLiterals' that can be used to fallback to the Spark 1.6 behavior regarding string literal parsing. For example, if the config is enabled, the …

Spark 4.1.0 - preview3 ScalaDoc - org.apache.spark.status.api.v1.ApplicationInfo

Spark Streaming is an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of live data streams. Data can be ingested from many sources like Kafka, …

Spark uses Hadoop client libraries for HDFS and YARN. Starting in version Spark 1.4, the project packages “Hadoop free” builds that lets you more easily connect a single Spark binary to any …