tensorflow on spark

I was in the study of TensorFlow, but also in their own notebooks to complete the installation, in the Pycharm to learn. But recently, in order to use Python's scientific computing environment, I uninstalled the previous environment and reinstalled the TensorFlow with Anaconda, which describes how the CPU version is installed.Prerequisite check: In Https://developer.nvidia.com/cuda-gpus confirm tha

We will go through several stages of installing the CUDA-9.0,CUDNN and TensorFlow CPUs as well as the TensorFlow GPU version. Finally we will install Pytorch with cuda-9.0. In the Marvel movie The Black Widow's "I fight this war, so you don't have to".Last night, April 29, 2018, I successfully installed the TensorFlow on Ubuntu 18.04. However, the key to installi

[Spark] [Python]spark example of obtaining Dataframe from Avro fileGet the file from the following address:Https://github.com/databricks/spark-avro/raw/master/src/test/resources/episodes.avroImport into the HDFS system:HDFs Dfs-put Episodes.avroRead in:Mydata001=sqlcontext.read.format ("Com.databricks.spark.avro"). Load ("Episodes.avro")Interactive Run Results:In

This article describes how to install TensorFlow in virtualenv mode on Ubuntu.Install Pip and virtualenv:# ubuntu/linux 64-bitsudo apt-get install python-pip python-dev python-virtualenv# Mac OS xsudo easy_install pipsudo pip I Nstall--upgrade virtualenvTo create a virtualenv virtual environment:Enter the parent directory where you want to install TensorFlow, and then execute the following command to establ

* Record the configuration process, the content is basically the configuration of the problems encountered in each step and the corresponding method found on the Internet, the format will be more confusing. Make some records for the younger brothers and sisters to build a new server to provide some reference (if the teacher to buy a new server), but also hope to help people in need. System configuration: CPU Xeon e5-2620 V3, Gpu:nvida TITAN X, Os:ubuntu 14.04 Laboratory to block Titan X, the s

"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 Installing IntelliJ IdeaIdea full name IntelliJ ideas, a Java language development integration Environment, IntelliJ is recognized as one of the best Java development tools in the industry, especially in smart Code helper, code auto hint, refactoring, Java EE support, Ant, JUnit, CVS integration, c

Spark example and spark example 1. Set up the Spark development environment in Java (fromHttp://www.cnblogs.com/eczhou/p/5216918.html) 1.1 jdk Installation Install jdk in oracle. I installed jdk 1.7. After installing the new system environment variable JAVA_HOME, the variable value is "C: \ Program Files \ Java \ jdk1.7.0 _ 79 ", depends on the installation path.

for Linux1.4 TensorFlow 0.11TensorFlow GitHub above mentioned 4 kinds of installation methods, this tutorial using the four source code installationVIRTUALENV InstallationAnaconda InstallationDocker InstallationInstalling from sourcesHttps://github.com/tensorflow/tensorflow ()Description: I chose the Linux GPU Python2(2) Click Python 2 to start the download.2. I

What to note: Install TensorFlow on Ubuntu (version python2.7)Note Date: 2018-01-31 Install TensorFlow on Ubuntu (version python2.7)My system environment: Ubuntu 16.04 LTS Python 2.7 Python 3.5 Two versions of TensorFlow:The TensorFlow is mainly installed in the following ways: Virtualenv Pip Docker Anaconda So

Spark Learning III: Installing and Importing source code for spark schedule and ideatags (space delimited): Spark Spark learns to install and import source code for three spark schedule and idea Data location during an RDD operation Two

The content of this lecture:A. Jobscheduler Insider implementationB. Jobscheduler Deep ThinkingNote: This lecture is based on the spark 1.6.1 version (the latest version of Spark in May 2016).Previous section ReviewLast lesson, we take the Jobgenerator class as the center of gravity, for everyone left and right extension, decryption job dynamic generation, and summed up the job dynamic generation of the thr

The spark kernel is developed by the Scala language, so it is natural to develop spark applications using Scala. If you are unfamiliar with the Scala language, you can read Web tutorials A Scala Tutorial for Java programmers or related Scala books to learn. This article will introduce 3 Scala spark programming examples, WordCount, TOPK, and Sparkjoin, representi

If you have to install hadoop my version hadoop2.3-cdh5.1.0 1. Download the maven package 2. Configure the m2_home environment variable and configure the maven bin directory to the path 3. Export maven_opts = "-xmx2g-XX: maxpermsize = 512 M-XX: reservedcodecachesize = 512 M" Download the spark-1.0.2.gz package and decompress it on the official website 5. Go to the Spark extract package directory. 6. Run./ma

Sparksql refers to the Spark-sql CLI, which integrates hive, essentially accesses the hbase table via hive, specifically through Hive-hbase-handler, as described in the configuration: Hive (v): Hive and HBase integrationDirectory: Sparksql Accessing HBase Configuration Test validation Sparksql to access HBase configuration: Copy the associated jar package for HBase to the $spark_home/lib directory on the

Objective　　After installing CDH and Coudera Manager offline, all of your own apps are installed through Coudera Manager, including HDFs, hive, yarn, Spark, hbase, and so on, and the process is a twist, so don't complain and go straight to the subject.Describe　　In the installation of Spark node, through the Spark-shell start S