上韩国网站梯子 Lightning-fast unified analytics engine

上韩国网站梯子
  • Spark 3.0.0 released (Jun 18, 2024)
  • Spark+AI Summit (June 22-25th, 2024, VIRTUAL) agenda posted (Jun 15, 2024)
  • Spark 2.4.6 released 上韩国网站梯子
  • Spark 2.4.5 released 上韩国网站梯子

Archive

上韩国网站梯子
Apache Spark™ is a unified analytics engine for large-scale data processing.

大哥云加速器npv-快连加速器app

Run workloads 100x faster.

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.

Logistic regression in Hadoop and Spark

大哥云加速器npv-快连加速器app

Write applications quickly in Java, Scala, Python, R, and SQL.

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.

df = spark.read.json("logs.json") df.上韩国网站梯子(上韩国网站梯子)   .select("name.first").show()
Spark's Python DataFrame API
Read JSON files with automatic schema inference

大哥云加速器npv-快连加速器app

Combine SQL, streaming, and complex analytics.

Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, 上韩国网站梯子, and Spark Streaming. You can combine these libraries seamlessly in the same application.

大哥云加速器npv-快连加速器app

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 上韩国网站梯子, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

大哥云加速器npv-快连加速器app

Spark is used at a wide range of organizations to process large datasets. You can find many example use cases on the Powered By page.

There are many ways to reach the community:

  • Use the mailing lists to ask questions.
  • In-person events include numerous meetup groups and conferences.
  • We use JIRA for issue tracking.

大哥云加速器npv-快连加速器app

Apache Spark is built by a wide set of developers from over 300 companies. Since 2009, more than 1200 developers have contributed to Spark!

The project's committers come from more than 25 organizations.

If you'd like to participate in Spark, or contribute to the libraries on top of it, learn how to contribute.

大哥云加速器npv-快连加速器app

Learning Apache Spark is easy whether you come from a Java, Scala, Python, R, or SQL background:

  • Download the latest release: you can run Spark locally on your laptop.
  • Read the quick start guide.
  • Learn how to deploy Spark on a cluster.
番茄免费小说娇骨,番茄免费阅读小说app下载,番茄免费听小说,番茄免费小说领取加速器  安卓软件,安卓加速软件,安卓加速器,酷通加速器官方下载  白鲸vp加速器,极光vp加速器,白鲸vp加速器官网,白熊vp加速器  在线测网速speed,speedtest在线测试网址,speedpdf官网入口,江苏宽带测速网页版  信捷官网文件打不开,信捷官网官网,心遇官网客服,信捷官网首页登录  黑洞加速器官方网站安卓,黑洞加速器官方网站,云帆加速器官网是什么,极光加速器官方网站下载