Apache Spark Tools

The Big data field of the 2014, Apache Spark (hereinafter referred to as Spark) is undoubtedly the most attention. Spark, from the hand of the family of Berkeley Amplab, at present by the commercial company Databricks escort. Spark has become one of ASF's most active projects since March 2014, and has received extensive support in the industry-the spark 1.2 release in December 2014 contains more than 1000 contributor contributions from 172-bit TLP ...

Spark is a memory-based, open-source cluster computing system designed for faster data analysis. Spark was developed using Scala by Matei, AMP Labs, University of California, Berkeley. The core part of the code is only 63 Scala files, which is very lightweight. Spark provides an open source clustered computing environment similar to Hadoop, but Spark performs better on some workloads based on memory and iteratively optimized designs. & nbs ...

April 19, 2014 Spark Summit China 2014 will be held in Beijing. The Apache Spark community members and business users at home and abroad will be gathered in Beijing for the first time. Spark contributors and front-line developers from AMPLab, Databricks, Intel, Taobao, NetEase, and others will share their Spark project experience and best practices in production environments. The following is a reporter interviewed the original: - What are the reasons to attract you to study Spark ...

The Apache Spark is a memory data processing framework that has now been upgraded to a Apche top-level project, which helps to improve spark stability and replace mapreduce status in the next generation of large data applications. Spark has recently been very strong, replacing the mapreduce trend. 　　This Tuesday, the Apache Software Foundation announced Spark upgraded to a top-level project. Because of its performance and speed due to mapreduce and easier to use, spark currently has a large user and ...

Spark is a cluster computing platform originating from the Amplab of the University of California, Berkeley, which is a rare versatile player, based on memory computing, starting with multiple iterations, and eclectic data warehousing, streaming and graph computing paradigms. Spark is now the Apache Foundation's top open source project, with a huge community support, technology is gradually maturing, but to really put into production, but also need to undergo a lot of optimization. To shark, Spark streaming and related projects as the theme, Spark Summ ...

Http://www.aliyun.com/zixun/aggregation/14112.html ">hortonworks's new code improved integration of Spark and Hive, 　　and plan for security and performance upgrades to the Spark memory analysis platform. The Apache Spark Memory analysis platform is now a hot technology in the field of large data analysis, and the Hadoop publisher Hortonworks recently decided to increase its commitment to spark. This week ...

Hadoop is a large data distributed system infrastructure developed by the Apache Foundation, the earliest version of which was the 2003 original Yahoo! Doug cutting is based on Google's published academic paper. Users can easily develop and run applications that process massive amounts of data in Hadoop without knowing the underlying details of the distribution. The features of low cost, high reliability, high scalability, high efficiency and high fault tolerance make Hadoop the most popular large data analysis system, yet its HDFs and mapred ...

The 2013 China Hadoop Summit Forum, following the October end of the Hadoop technology, the largest company in the United States Cloudera Company announced and Databricks cooperation, providing the Apache Spark Computing framework of technical support, the local large data platform software company Star-ring information technology ( Shanghai) Co., Ltd. (hereinafter referred to as "star-ring technology") took the lead in the domestic launch of a large data platform products transwarp, the integration of Apache Spark and Apache Hadoop 2 ....

Currently, the Hadoop distribution has an open source version of Apache and a Hortonworks distribution (HDP Hadoop), MapR Hadoop, and so on. All of these distributions are based on Apache Hadoop.

This time, we share the 13 most commonly used open source tools in the Hadoop ecosystem, including resource scheduling, stream computing, and various business-oriented scenarios. First, we look at resource management.