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Apache Spark™ is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. |
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# What is Apache Spark™? | ||
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Apache Spark™ is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. 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. | ||
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%%LOGO%% | ||
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## Online Documentation | ||
You can find the latest Spark documentation, including a programming guide, on the [project web page](https://spark.apache.org/documentation.html). This README file only contains basic setup instructions. | ||
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## Interactive Scala Shell | ||
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The easiest way to start using Spark is through the Scala shell: | ||
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``` | ||
docker run -it spark /opt/spark/bin/spark-shell | ||
``` | ||
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Try the following command, which should return 1,000,000,000: | ||
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``` | ||
scala> spark.range(1000 * 1000 * 1000).count() | ||
``` | ||
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## Interactive Python Shell | ||
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The easiest way to start using PySpark is through the Python shell: | ||
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``` | ||
docker run -it spark:python3 /opt/spark/bin/pyspark | ||
``` | ||
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And run the following command, which should also return 1,000,000,000: | ||
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``` | ||
>>> spark.range(1000 * 1000 * 1000).count() | ||
``` | ||
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## Interactive R Shell | ||
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The easiest way to start using R on Spark is through the R shell: | ||
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``` | ||
docker run -it apache/spark-r /opt/spark/bin/sparkR | ||
``` | ||
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## Running Spark on Kubernetes | ||
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https://spark.apache.org/docs/latest/running-on-kubernetes.html | ||
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[Apache Spark™ community](https://spark.apache.org/community.html) |
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https://github.com/apache/spark-docker |
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https://issues.apache.org/jira/browse/SPARK |
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Apache Spark, Spark, Apache, the Apache feather logo, and the Apache Spark project logo are trademarks of The Apache Software Foundation. | ||
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Licensed under the [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0). |
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[Apache Spark](https://spark.apache.org/committers.html) |