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R language ︱h2o Some R language practices for deep learning--H2O Package

Several application cases of R language H2O packageAuthor's message: Inspired to understand the H2O platform of some R language implementation, online has a H2O demo file. I post some cases here, and put some small examples of their own practice.About H2O platform long what kind, can see H2O's official website, about d

Source Installation H2O Http Server program to Ubuntu servers

First install the family bucketApt install-y build-essential zlib1g-dev libpcre3 libpcre3-dev unzip cmake libncurses5-dev Libpam0g-dev Bison libboost-de V Libssl-dev OpenSSL g++ libxml2-dev libcurl3-openssl-dev libpng-dev libpng12-dev libfreetype6-dev Libfreetype6-devTo download the installation package:Curl Https://github.com/h2o/h2o/archive/v2.2.2.tar.gz-o v2.2.2.tar.gzExtract:Tar zxf v2.2.2.tar.gzTo conf

Spark cultivation (advanced)-Spark beginners: Section 13th Spark Streaming-Spark SQL, DataFrame, and Spark Streaming

Spark cultivation (advanced)-Spark beginners: Section 13th Spark Streaming-Spark SQL, DataFrame, and Spark StreamingMain Content: Spark SQL, DataFrame and Spark Streaming1.

Spark cultivation Path (advanced)--spark Getting started to Mastery: 13th Spark Streaming--spark SQL, dataframe and spark streaming

Label:Main content Spark SQL, Dataframe, and spark streaming 1. Spark SQL, dataframe and spark streamingSOURCE Direct reference: https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/ex

(upgraded) Spark from beginner to proficient (Scala programming, Case combat, advanced features, spark core source profiling, Hadoop high end)

This course focuses onSpark, the hottest, most popular and promising technology in the big Data world today. In this course, from shallow to deep, based on a large number of case studies, in-depth analysis and explanation of Spark, and will contain completely from the enterprise real complex business needs to extract the actual case. The course will cover Scala programming, spark core programming,

Spark Starter Combat Series--7.spark Streaming (top)--real-time streaming computing Spark streaming Introduction

"Note" This series of articles, as well as the use of the installation package/test data can be in the "big gift –spark Getting Started Combat series" get1 Spark Streaming Introduction1.1 OverviewSpark Streaming is an extension of the Spark core API that enables the processing of high-throughput, fault-tolerant real-time streaming data. Support for obtaining data

Architecture practices from Hadoop to spark

, there are other different problems with spark, but since Spark is open source, most problems can be solved with source code reading and the help of the open source community.Plan for the next stepSpark has made great strides in the 2014, and the big data ecosystem around spark has grown. Spark 1.3 introduces a new Da

[Reprint] Architecture practices from Hadoop to spark

problems can be solved with source code reading and the help of the open source community.Plan for the next stepSpark has made great strides in the 2014, and the big data ecosystem around spark has grown. Spark 1.3 introduces a new Dataframe API, a new Dataframe API that will make spark more user-friendly with data. The distributed cache system, also derived fro

Spark Starter Combat Series--2.spark Compilation and Deployment (bottom)--spark compile and install

"Note" This series of articles and the use of the installation package/test data can be in the "big gift--spark Getting Started Combat series" Get 1, compile sparkSpark can be compiled in SBT and maven two ways, and then the deployment package is generated through the make-distribution.sh script. SBT compilation requires the installation of Git tools, and MAVEN installation requires MAVEN tools, both of which need to be carried out under the network,

Spark Starter Combat Series--2.spark Compilation and Deployment (bottom)--spark compile and install

"Note" This series of articles and the use of the installation package/test data can be in the "big gift--spark Getting Started Combat series" Get 1, compile sparkSpark can be compiled in SBT and maven two ways, and then the deployment package is generated through the make-distribution.sh script. SBT compilation requires the installation of Git tools, and MAVEN installation requires MAVEN tools, both of which need to be carried out under the network,

Spark Asia-Pacific Research series "Spark Combat Master Road"-3rd Chapter Spark Architecture design and Programming Model Section 3rd: Spark Architecture Design (2)

Three, in-depth rddThe Rdd itself is an abstract class with many specific implementations of subclasses: The RDD will be calculated based on partition: The default partitioner is as follows: The documentation for Hashpartitioner is described below: Another common type of partitioner is Rangepartitioner: The RDD needs to consider the memory policy in the persistence: Spark offers many storagelevel

Spark cultivation Path--spark learning route, curriculum outline

Course Content Spark cultivation (Basic)--linux Foundation (15), Akka distributed programming (8 Speak) Spark Cultivation (Advanced)--spark Introduction to Mastery (30 speak) Spark cultivation Path (actual combat)--spark application Development Practice (20

[Spark] Spark Application Deployment Tools Spark-submit__spark

1. Introduction The Spark-submit script in the Spark Bin directory is used to start the application on the cluster. You can use the Spark for all supported cluster managers through a unified interface, so you do not have to specifically configure your application for each cluster Manager (It can using all Spark ' s su

[Spark Asia Pacific Research Institute Series] the path to spark practice-Chapter 1 building a spark cluster (Step 3) (2)

Install spark Spark must be installed on the master, slave1, and slave2 machines. First, install spark on the master. The specific steps are as follows: Step 1: Decompress spark on the master: Decompress the package directly to the current directory: In this case, create the spa

[Spark Asia Pacific Research Institute Series] the path to spark practice-Chapter 1 building a spark cluster (step 4) (1)

Step 1: Test spark through spark Shell Step 1:Start the spark cluster. This is very detailed in the third part. After the spark cluster is started, webui is as follows: Step 2:Start spark shell: In this case, you can view the shell in the following Web console: Step 3:Co

[Spark Asia Pacific Research Institute Series] the path to spark practice-Chapter 1 building a spark cluster (Step 3) (2)

Install spark Spark must be installed on the master, slave1, and slave2 machines. First, install spark on the master. The specific steps are as follows: Step 1: Decompress spark on the master: Decompress the package directly to the current directory: In this case, create the

Spark cultivation Path (advanced)--spark Getting Started to Mastery: section II Introduction to Hadoop, Spark generation ring

The main contents of this section Hadoop Eco-Circle Spark Eco-Circle 1. Hadoop Eco-CircleOriginal address: http://os.51cto.com/art/201508/487936_all.htm#rd?sukey= a805c0b270074a064cd1c1c9a73c1dcc953928bfe4a56cc94d6f67793fa02b3b983df6df92dc418df5a1083411b53325The key products in the Hadoop ecosystem are given:Image source: http://www.36dsj.com/archives/26942The following is a brief introduction to the products1 HadoopApache's Hadoop p

Different Swiss Army knives: vs. Spark and MapReduce

makes Spark behave as well as batch processing on real-time processing. This also gives rise to a better opportunity to solve all problems with a single platform rather than just selecting different platforms based on the task, after all, all platforms need to learn and maintain.Hadoop MapReduce is outstanding on batch processing. If you need to do real-time processing, you can use another platform like Storm or Impala, and figure processing can use

Spark Learning Note 6-spark Distributed Build (5)--ubuntu Spark distributed build

command:Add the following content, including the bin directory to the pathMake it effective with source1.4 Verification The input Scala version can be displayed as follows:Scala can also be programmed directly with Scala:2. Install Spark 2.1 Downloads Spark Download Address:Http://spark.apache.org/downloads.htmlFor learning purposes, I downloaded the pre-compiled version 1.6.2.2 Decompression The download

"Original Hadoop&spark Hands-on 5" Spark Basics Starter, cluster build and Spark Shell

Introduction to spark Basics, cluster build and Spark ShellThe main use of spark-based PPT, coupled with practical hands-on to enhance the concept of understanding and practice.Spark Installation DeploymentThe theory is almost there, and then the actual hands-on experiment:Exercise 1 using Spark Shell (native mode) to

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