Spark Streaming

Spark Streaming

Apache Software Foundation
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About

PySpark is an interface for Apache Spark in Python. It not only allows you to write Spark applications using Python APIs, but also provides the PySpark shell for interactively analyzing your data in a distributed environment. PySpark supports most of Spark’s features such as Spark SQL, DataFrame, Streaming, MLlib (Machine Learning) and Spark Core. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrame and can also act as distributed SQL query engine. Running on top of Spark, the streaming feature in Apache Spark enables powerful interactive and analytical applications across both streaming and historical data, while inheriting Spark’s ease of use and fault tolerance characteristics.

About

Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part. By running on Spark, Spark Streaming lets you reuse the same code for batch processing, join streams against historical data, or run ad-hoc queries on stream state. Build powerful interactive applications, not just analytics. Spark Streaming is developed as part of Apache Spark. It thus gets tested and updated with each Spark release. You can run Spark Streaming on Spark's standalone cluster mode or other supported cluster resource managers. It also includes a local run mode for development. In production, Spark Streaming uses ZooKeeper and HDFS for high availability.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Application development solution for DevOps teams

Audience

Real-Time Data Streaming solution for businesses

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

PySpark
spark.apache.org/docs/latest/api/python/

Company Information

Apache Software Foundation
Founded: 1999
United States
spark.apache.org/streaming/

Alternatives

Alternatives

ksqlDB

ksqlDB

Confluent
Samza

Samza

Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation
Spark Streaming

Spark Streaming

Apache Software Foundation
MLlib

MLlib

Apache Software Foundation

Categories

Categories

Integrations

Apache Spark Supported
Amazon SageMaker Data Wrangler Supported
Comet LLM Supported
Feast Supported
Fosfor Decision Cloud Supported
PubSub+ Platform Not Supported
Tecton Supported
Union Pandera Supported

Integrations

Apache Spark Supported
Amazon SageMaker Data Wrangler Not Supported
Comet LLM Not Supported
Feast Not Supported
Fosfor Decision Cloud Not Supported
PubSub+ Platform Supported
Tecton Not Supported
Union Pandera Not Supported
Claim PySpark and update features and information
Claim PySpark and update features and information
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