Learn how to write distributed queries using LINQ to Spark, a library that enables you to use LINQ syntax with Apache Spark for large-scale data analysis and machine learning.

Learn how to use Spark's components, such as Spark Streaming, Spark Structured Streaming, Spark SQL, Spark MLlib, and Spark GraphX, to perform real-time analytics on streaming data.

SQL (Structured Query Language) is the most common and widely used language for querying and defining data. Spark SQL functions as an extension to Apache Spark for processing structured data, using ...

The Spark ecosystem can also solve graph computations (via GraphX), streaming (real-time calculations), and real-time interactive query processing with Spark SQL and DataFrames.

I have put content of my test_sql_query_automation.py exactly as in the malexer's test/test_spark_session_fixture.py here in master branch. To easily reproduce this you may want to use the same Docker ...

Spark SQL. Spark SQL has become more and more important to the Apache Spark project. It is the interface most commonly used by today’s developers when creating applications. Spark SQL is focused ...

Spark SQL. Spark SQL allows users to run SQL queries on large datasets. It integrates seamlessly with DataFrames and enables querying structured data stored in various formats like JSON Parquet ORC ...

With Apache Spark Declarative Pipelines, engineers describe what their pipeline should do using SQL or Python, and Apache Spark handles the execution.