Spark SQL

Spark SQL is Apache Spark’s interface for working with structured and semistructured data.

Key Features of the Spark SQL Snap Pack

Organizations using Big Data to make better business decisions and using Spark SQL to write, read, and query data inside a Spark program can use the Spark SQL Snap Pack to manage data in their Big Data environments. Use the Spark SQL Snaps to format data from HDFS, Parquet, ORC, CSV, and other types of files, and conduct various actions to better manage data within a Big Data environment. Once the data is partitioned, aggregated or filtered, it’s ready for analysis, leading to business innovation and revenue opportunities.

The Spark SQL Snap Pack includes the following Snaps:

  • Expression Language
  • Aggregate
  • Avro Formatter
  • Avro Parser
  • Cache
  • Catalog Reader/Writer
  • Copy
  • CSV Formatter
  • CSV Parser
  • Diff
  • Execute
  • Filter
  • HDFS Reader/Writer
  • Intersect
  • Join
  • JSON Formatter
  • JSON Parser
  • Limit
  • LineReader
  • ORC Formatter
  • ORC Parser
  • Parquet Formatter
  • Parquet Parser
  • Pivot
  • Repartition
  • Router
  • Sort
  • Transform
  • Union
  • Unique

Learn more about how Snaps work with the SnapLogic Enterprise Integration Cloud.

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