Tag: blog http OS file 2014 Art
Preface:
Spark has been very popular recently. This article does not talk about spark principles, but studies how to compile spark cluster construction and service scripts. We hope to understand spark clusters from the perspective of running scripts.
Yahoo's spark practice
Yahoo is one of the big data giants who have a unique passion for spark. This summit, Yahoo contributed three speeches, let us one by one.
Andy Feng, a prominent Yahoo architect from the University of Zhejiang , tried to answer two questions in his keynote speech.
First question, why Yahoo falls in love with Spark. Machine learning, Data
Tags: AOP org jmx example init exec 2.0 lines www.1. Prepare for Work 1.1 install spark and configure spark-env.shYou need to install spark before using Spark-shell, please refer to http://www.cnblogs.com/swordfall/p/7903678.htmlIf you use only one node, you can not configure the slaves file, the
Install TensorFlow in virtualenv mode on Ubuntu
This article describes how to install tensorflow in virtualenv mode on Ubuntu.
Install pip and virtualenv:
# Ubuntu/Linux 64-bit
Sudo apt-get install python-pip python-dev python-virtualenv
# Mac OS X
Sudo easy_install pip
Sudo pip install -- upgrade virtualenv
Create a Virtualenv virtual environment:
Go to the parent directory where you want to install
Install TensorFlow in Python2.7 in Ubuntu 16.04
My system environment:
Ubuntu 16.04 LTS
Python 1, 2.7
Python 1, 3.5
Two TensorFlow versions:
TensorFlow is installed in the following ways:
Virtualenv
Pip
Docker
Anaconda
Source code compilation
Pip is the Python software package management system: Pip Install Packages recursive abbreviation
The Command
Recently saw a post on the spark architecture, the author is Alexey Grishchenko. The students who have seen Alexey blog should know that he understands spark very deeply, read his "spark-architecture" this blog, a kind of clairvoyant feeling, from the JVM memory allocation to the Spark cluster resource management, step
The company launched the online project Spark has nearly 1 over time. Effective, spark in fact, excellent distributed computing platform to improve productivity.Start this note. The previous seminar Spark Research Report was shared (it will be divided into articles due to space limitations), in order to help friends who have just contacted
Article Source: http://www.dataguru.cn/thread-331456-1-1.html
Today you want to make an error in the Yarn-client state of Spark-shell:[Python] View plaincopy [Hadoop@localhost spark-1.0.1-bin-hadoop2]$ Bin/spark-shell--master yarn-client Spark Assembly has been Built with Hive, including DataNucleus jars on classpath
Original link: http://www.raincent.com/content-85-11052-1.html
In the field of large data, only deep digging in the field of data science, to walk in the academic forefront, in order to be in the underlying algorithms and models to walk in front of, and thus occupy the leading position. Source: Canada Rice Valley Large dataIn the field of large data, only deep digging in the field of data science, to walk in the academic forefront, in order to be in the underlying algorithms and models to walk i
1. Optimization? Why? How? When? What?
"Spark applications also need to be optimized. "Many people may have this question," not already have code generators, executive optimizer, pipeline or something. ”。 Yes, Spark does have some powerful built-in tools to make your code faster when it executes. But if everything depends on the tools, framework to do, I think that can only illustrate two questions: you a
Tags: create NTA rap message without displaying cat stream font1. What is Spark streaming?A, what is Spark streaming?Spark streaming is similar to Apache Storm, and is used for streaming data processing. According to its official documentation, Spark streaming features high throughput and fault tolerance.
TensorFlow installation is divided into two cases, one is CPU only, and the other is the use of the GPU, which also installs Cuda and CUDNN, the situation is relatively complex. The above two categories recommend using Anaconda as the Python environment, and the basic version of Python is version 3.5. This article is to give the Conda environment configuration installation of TensorFlow, you can not install
path under the Scala installation directory is added to the system variable path, similar to the above JDK installation step), In order to verify that the installation was successful, open a new CMD window, enter it, scala and return it, if you can enter the Scala Interactive command environment, the installation is successful. As shown in the following:Note: If you cannot display version information and do not enter Scala's interactive command line, there are usually two possibilities:1. The
Spark Learning six: Spark streamingtags (space delimited): Spark
Spark learning six spark streaming
An overview
Case study of two enterprises
How the three spark streaming works
Application of
TaskOnline blacklist filter for ad clicksUsenc -lk 9999Enter some data on the data send port, such as:1375864674543 Tom1375864674553 Spy1375864674571 Andy1375864688436 Cheater1375864784240 Kelvin1375864853892 Steven1375864979347 JohnCodeImportOrg.apache.spark.SparkConfImportOrg.apache.spark.streaming.StreamingContextImportOrg.apache.spark.streaming.Seconds Object onlineblacklistfilter { defMain (args:array[string]) {/** * Step 1th: Create a Configuration object for
TensorFlow is an open source software library that uses data flow diagrams for numerical calculations. In other words, that's the best way to build a deep learning model. This article collates some excellent tutorials and a list of projects on TensorFlow.
First, the tutorial
TensorFlow Tutorial 1-from basics to more interesting
You are welcome to reprint it. Please indicate the source.Summary
The SQL module was added to the newly released spark 1.0. What's more interesting is that hiveql in hive also provides good support, as a source code analysis control, it is very interesting to know how spark supports hql.Introduction to hive
The following part is taken from hive in hadoop definite guide.
"Hive was designed by Facebook to all
This article mainly describes some of the operations of Spark standalone mode for job migration to spark on yarn. 1, Code RECOMPILE
Because the previous Spark standalone project used the version of Spark 1.5.2, and now spark on yarn is using
Because Spark is implemented in Scala, spark natively supports the Scala API. In addition, Java and Python APIs are supported.For example, the Python API for the Spark 1.3 version. Its module-level relationships, for example, are as seen in:As you know, Pyspark is the top-level package for the Python API, which includes several important subpackages. Of1) Pyspark
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