Apache SparkApache Software Foundation
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Related Products
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About
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.
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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.
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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
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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
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Audience
Organizations that want a unified analytics engine for large-scale data processing
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Audience
Application development solution for DevOps teams
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Not Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Supported
Free Trial
Not Supported
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Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationApache Software Foundation
Founded: 1999
United States
spark.apache.org
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Company InformationPySpark
spark.apache.org/docs/latest/api/python/
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Categories |
Categories |
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Streaming Analytics Features
Data Enrichment
Supported
Data Wrangling / Data Prep
Supported
Multiple Data Source Support
Supported
Process Automation
Supported
Real-time Analysis / Reporting
Not Supported
Visualization Dashboards
Not Supported
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Integrations
Amazon SageMaker Data Wrangler
Supported
Amazon EC2
Supported
Amazon SageMaker Feature Store
Supported
Amundsen
Supported
Apache Kylin
Supported
Apache Mahout
Supported
BentoML
Supported
Coginiti
Supported
Dagster
Supported
E2E Cloud
Supported
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Integrations
Amazon SageMaker Data Wrangler
Supported
Amazon EC2
Not Supported
Amazon SageMaker Feature Store
Not Supported
Amundsen
Not Supported
Apache Kylin
Not Supported
Apache Mahout
Not Supported
BentoML
Not Supported
Coginiti
Not Supported
Dagster
Not Supported
E2E Cloud
Not Supported
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