Apache Hadoop (Core)
Hortonworks Data Platform (HDP) helps enterprises gain insights from structured and unstructured data. It is an open source framework for distributed storage and processing of large, multi-source data sets. Download the Hortonworks Data Platform (HDP). Note: this artifact is located at Mapr repository (https://repository.mapr.com/nexus/content/groups/mapr-public/releases/). 5.1 - Could not locate executable nullbinwinutils.exe 2018-06-04 20:23:33 ERROR Shell:397 - Failed to locate the winutils binary in the hadoop binary path java.io.IOException: Could not locate executable nullbinwinutils.exe in the Hadoop binaries. Solved: I want to execute './sbin/start-master.sh', but I'm unable to locate this file in the /sbin folder. I wanted to find the file using.
Randy Orton - DDT. At the top place in the best WWE finishing moves of all time, we have DDT. This is a list of (almost!) every finishing move in the WWE and WWF. Wrestlers who are not currently with the WWE are still included, but wrestlers who have never been on a WWE/WWF roster are not. Wwe all stars finishing moves. 40 WWE finishing maneuvers Take a closer look at 40 of WWE's most famous finishing maneuvers, featuring the signature moves of today's top Superstars. Check out these screenshots and videos showcasing the finishing moves from WWE All Stars. The game is set for release on March 29th in North America and a couple of days later in Europe.
Reliable, scalable distributed storage and computing
Apache Accumulo
A secure, distributed data store to serve performance-intensive Big Data applications
Apache Flume
For collecting and aggregating log and event data and real-time streaming it into Hadoop
Apache HBase
All things fair 1995. Scalable record and table storage with real-time read/write access
Apache Hive
Familiar SQL framework with metadata repository for batch processing of Hadoop data
HUE
The extensible web GUI that makes Hadoop users more productive
Apache Impala
The data warehouse native to Hadoop for low-latency queries under multi-user workloads
Apache Kafka®
The backbone for distributed real-time processing of Hadoop data
Apache Pig
High-level data flow language for processing data stored in Hadoop
Apache Sentry
Fine-grained, role-based authorization for Impala and Hive
Reliable, scalable distributed storage and computing
Apache Accumulo
A secure, distributed data store to serve performance-intensive Big Data applications
Apache Flume
For collecting and aggregating log and event data and real-time streaming it into Hadoop
Apache HBase
All things fair 1995. Scalable record and table storage with real-time read/write access
Apache Hive
Familiar SQL framework with metadata repository for batch processing of Hadoop data
HUE
The extensible web GUI that makes Hadoop users more productive
Apache Impala
The data warehouse native to Hadoop for low-latency queries under multi-user workloads
Apache Kafka®
The backbone for distributed real-time processing of Hadoop data
Apache Pig
High-level data flow language for processing data stored in Hadoop
Apache Sentry
Fine-grained, role-based authorization for Impala and Hive
Cloudera Search
Powered by Solr to make Hadoop accessible to everyone via integrated full-text search
Apache Spark™
The open standard for in-memory batch and real-time processing for advanced analytics Everlast 950 elliptical.
Apache Sqoop
Data transport engine for integrating Hadoop with relational databases
- Java 8 : We are going to use the Java 8 Function interface and the hot Lambda expressions.
- Maven 3 : Just to automate collecting the project dependencies.
- Eclipse : My usual IDE for Java/JavaEE developments.
Hortonworks Winutils.exe Download
- Download the executable winutils from the Hortonworks repository.
- Create a dummy directory where you place the downloaded executable winutils.exe. For example : C:SparkDevbin.
- Add the environment variable HADOOP_HOME which points to C:SparkDev. You have 2 choices :
- Windows > System Setting
- Eclipse > Your Class which can be run as a Java Application (containing the static main method) > Right Click > Run as > Run Configurations > Evironment Tab :
Hortonworks Winutils.exe
Create a Maven Project. Configure pom.xml as follows :
Hortonworks Winutils
The benefit of creating a local Spark context is the possibility to run everything locally without being in need of deploying Spark Server separately as a master. This is very interesting while development phase. So here it is the basic configuration :
Now that we have an operational environment, let's move to punchy examples of RDD Tranformations and Actions tutorial.
