Skip to main content

Spark

Apache Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, pandas API on Spark for pandas workloads, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.

Document loaders​

PySpark​

It loads data from a PySpark DataFrame.

See a usage example.

from langchain_community.document_loaders import PySparkDataFrameLoader

Tools/Toolkits​

Spark SQL toolkit​

Toolkit for interacting with Spark SQL.

See a usage example.

from langchain_community.agent_toolkits import SparkSQLToolkit, create_spark_sql_agent
from langchain_community.utilities.spark_sql import SparkSQL

Spark SQL individual tools​

You can use individual tools from the Spark SQL Toolkit:

  • InfoSparkSQLTool: tool for getting metadata about a Spark SQL
  • ListSparkSQLTool: tool for getting tables names
  • QueryCheckerTool: tool uses an LLM to check if a query is correct
  • QuerySparkSQLTool: tool for querying a Spark SQL
from langchain_community.tools.spark_sql.tool import InfoSparkSQLTool
from langchain_community.tools.spark_sql.tool import ListSparkSQLTool
from langchain_community.tools.spark_sql.tool import QueryCheckerTool
from langchain_community.tools.spark_sql.tool import QuerySparkSQLTool

Was this page helpful?


You can also leave detailed feedback on GitHub.