tensorflow on spark

Step 5: test the spark IDE development environment The following error message is displayed when we directly select sparkpi and run it: The prompt shows that the master machine running spark cannot be found. In this case, you need to configure the sparkpi execution environment: Select Edit configurations to go to the configuration page: In program arguments, enter "local ": This configuration i

Next package, use Project structure's artifacts:Using the From modules with dependencies:Select Main Class:Click "OK":Change the name to Sparkdemojar:Because Scala and spark are installed on each machine, you can delete both Scala and spark-related jar files:Next Build:Select "Build Artifacts":The rest of the operation is to upload the jar package to the server, and then execute the

Reason:Running the spark code with the root userWorkaround: Run spark with a non-administrator account[[Email protected] Bin]$./Add-User.ShWhatType of userDoYou wish to add?A) Management User (Mgmt-Users.Properties)B) Application User (Application-Users.Properties)(A):BEnterThe details of theNewUser to add.Realm (Applicationrealm) : Applicationrealm ---->> Careful Here . YouNeed to typeThisor leave it blank

/49/D5/wKioL1QbpNKDWXo_AAElnZLjV4U229.jpg "style =" float: none; "Title =" 14.png" alt = "wkiol1qbpnkdwxo_aaelnzljv4u229.jpg"/> Select "yes" to enable automatic installation of scala plug-in idea. 650) This. width = 650; "src =" http://s3.51cto.com/wyfs02/M00/49/D3/wKiom1QbpLijqttNAAE3LTevJ5I077.jpg "style =" float: none; "Title =" 15.png" alt = "wkiom1qbplijqttnaae3ltevj5i077.jpg"/> In this case, it takes about 2 minutes to download and install the SDK. Of course, the download time varies depen

; "src =" http://s3.51cto.com/wyfs02/M02/4A/13/wKioL1QiJJPzxOm0AAFxk_FS8AU762.jpg "style =" float: none; "Title =" 51.png" alt = "wkiol1qijjpzxom0aafxk_fs8au762.jpg"/> We found that we fully used the new background and correctly ran the program, which is much faster than the first operation. This article is from the spark Asia Pacific Research Institute blog, please be sure to keep this source http://rockyspark.blog.51cto.com/2229525/1557591 [

Share with you what spark is? How to analyze data with spark, and small partners who are interested in big data to learn about it.Big Data Online LearningWhat is Apache Spark?Apache Spark is a cluster computing platform designed for speed and general purpose.From a speed point of view,

Save and run the source command to make the configuration file take effect. Step 3: Run idea and install and configure the idea Scala development plug-in: The official document states: Go to the idea bin directory: Run "idea. Sh" and the following page appears: Select "Configure" To Go To The idea configuration page: Select plugins To Go To The plug-in installation page: Click the "Install jetbrains plugin" option in the lower left corner to go to the following page: Enter "Scala"

Modify the source code of our "firstscalaapp" to the following: Right-click "firstscalaapp" and choose "Run Scala console". The following message is displayed: This is because we have not set the JDK path for Java. Click "OK" to go to the following view: In this case, select the "project" option on the left: In this case, we select "new" of "No SDK" to select the following primary View: Click the JDK option: Select the JDK directory we installed earlier: Click "OK" Click OK: Click the f

-site.xml configuration can refer: Http://hadoop.apache.org/docs/r2.2.0/hadoop-mapreduce-client/hadoop-mapreduce-client-core/mapred-default.xml Step 7 modify the profile yarn-site.xml, as shown below: Modify the content of the yarn-site.xml: The above content is the minimal configuration of the yarn-site.xml, the content of the yarn-site.xml file configuration can be referred: Http://hadoop.apache.org/docs/r2.2.0/hadoop-yarn/hadoop-yarn-common/yarn-default.xml [

Label: style blog http OS Using Ar Java file sp Download the downloaded"Hadoop-2.2.0.tar.gz "Copy to"/Usr/local/hadoop/"directory and decompress it: Modify the system configuration file ~ /Configure "hadoop_home" in the bashrc file and add the bin folder under "hadoop_home" to the path. After modification, run the source command to make the configuration take effect. Next, create a folder in the hadoop directory using the following command: Next, modify the hadoop configuration file. F

Label: style blog http OS use AR file SP 2014 7. perform the same hadoop 2.2.0 operations on sparkworker1 and sparkworker2 as sparkmaster. We recommend that you use the SCP command to copy the hadoop content installed and configured on sparkmaster to sparkworker1 and sparkworker2; 8. Start and verify the hadoop distributed Cluster Step 1: format the HDFS File System: Step 2: Start HDFS in sbin and execute the following command: The startup process is as follows: At this point, we

Copy the downloaded hadoop-2.2.0.tar.gz to the "/usr/local/hadoop/" directory and decompress it: Modify the system configuration file ~ /Configure "hadoop_home" in the bashrc file and add the bin folder under "hadoop_home" to the path. After modification, run the source command to make the configuration take effect. Next, create a folder in the hadoop directory using the following command: Next, modify the hadoop configuration file. First, go to the hadoop 2.2.0 configuration file area:

Download the downloaded"Hadoop-2.2.0.tar.gz "Copy to"/Usr/local/hadoop/"directory and decompress it: Modify the system configuration file ~ /Configure "hadoop_home" in the bashrc file and add the bin folder under "hadoop_home" to the path. After modification, run the source command to make the configuration take effect. Next, create a folder in the hadoop directory using the following command: \Next, modify the hadoop configuration file. First, go to the hadoop 2.2.0 configuration file

Http://www.cnblogs.com/shishanyuan/archive/2015/08/19/4721326.html 1, spark operation structure 1.1 term definitions LApplication: The Spark application concept is similar to that of the Hadoop mapreduce, which refers to a user-written Spark application that contains a driver Functional code and executor code that runs on multiple nodes in a cluster; LDrive

November 9, 2015 Google Open source of the artificial intelligence platform TensorFlow, but also become the 2015 's most popular open source projects. After 12 iterations from v0.1 to v0.12, Google released its version of TensorFlow 1.0 on February 15, 2017, and hosted the first TensorFlow Dev Summit conference in Mountain View, California, USA.

As a result of the recent busy, until the holidays are empty, so will learn from their own knowledge to share. If there is a wrong place, please point out, thank you! At present the deep study is getting more and more fire, the related worker who learns, uses TensorFlow more and more. Recently, a Python script was used to train the model under the TensorFlow line, and the Freeze_graph tool was used to outpu

Brief Introduction Tensorflow-bitcoin-robot: A Bitcoin price prediction robot based on the TensorFlow lstm model. The article includes a few parts:1. Why try to do this project.2. Why did you choose this model?3. Where does the data from the model come from.4. The optimization process of the model.5. The direction in which the project can be further improved. The recent performance of the digital currency,

I. Recommended TWO websites TensorFlow Official Document: Https://www.tensorflow.org/install/install_windows TensorFlow Chinese Community: http://www.tensorfly.cn/tfdoc/get_started/os_setup.html Two. install TensorFlow on WindowsDirectory: Determine the TensorFlow to install Requirements

Build Ubantu machine on VirtualBox, install Anaconda,java 8,spark,ipython Notebook, and WordCount example program with Hello World. Build Spark EnvironmentIn this section we learn to build a spark environment: Create an isolated development environment on an Ubuntu 14.04 virtual machine without affecting any existing systems Installs

This article directory Introduction based on Anaconda tensorflow install 1 download Linux version of Anaconda installation package 2 Install Anaconda use Anaconda installation TensorFlow 1 establish a Conda computing environment 2 activation environment using Conda installation TensorFlow 3 Installation TensorFlow 4 Ho