List of Pages in Category Spark (52 pages)
Spark
Apache Spark is a general framework for distributed computing that offers high performance for both batch and interactive processing. It exposes APIs for Java, Python, and Scala and consists of Spark core and several related projects:
- Spark SQL - Module for working with structured data. Allows you to seamlessly mix SQL queries with Spark programs.
- Spark Streaming - API that allows you to build scalable fault-tolerant streaming applications.
- MLlib - API that implements common machine learning algorithms.
- GraphX - API for graphs and graph-parallel computation.
Cloudera supports Spark core, Spark SQL (including DataFrames), Spark Streaming, and MLlib. Cloudera does not currently offer commercial support for GraphX or SparkR.
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- Accessing Avro Data Files From Spark SQL Applications
- Accessing Data Stored in Amazon S3 through Spark
- Accessing Data Stored in Azure Data Lake Store (ADLS) through Spark
- Accessing External Storage from Spark
- Accessing Parquet Files From Spark SQL Applications
- Apache Spark Overview
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- CDH 5 and Cloudera Manager 5 Requirements and Supported Versions
- Configuring ADLS Connectivity
- Configuring Spark Applications
- Configuring Spark on YARN for Long-Running Applications
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- Managing Spark
- Managing Spark Standalone Using the Command Line
- Managing Spark Using Cloudera Manager
- Managing the Spark History Server
- Monitoring Spark Applications
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- Running Apache Hive on Spark in CDH
- Running Spark Applications
- Running Spark Applications on YARN
- Running Spark Python Applications
- Running Your First Spark Application
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- Spark (Standalone) Metrics
- Spark 2 Metrics
- Spark and Hadoop Integration
- Spark and IPython and Jupyter Notebooks
- Spark Application Overview
- Spark Authentication
- Spark Encryption
- Spark Guide
- Spark Indexing
- Spark Installation
- Spark Metrics
- Spark Packages
- Spark Prerequisites
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