Big Data and AWS #Big Data

AWS Concepts and Tools for Big Data Implementation

Amazon Kinesis
Big Data Streaming and Amazon Kinesis
Example: Using Amazon Kinesis to Stream and Analyze Apache Server Log Data

Amazon Athena
Big Data Processing and Analytics
Example: Using Amazon Athena to Query Log Data From Amazon S3

DynamoDB
No SQL DBMS: Storing and Querying Data on Amazon DynamoDB

Amazon EMR:
Apache Hadoop and Amazon EMR
Using Amazon EMR
Hadoop Programming Frameworks
Example: Processing Server Logs With Hive on Amazon EMR

Web Interfaces on Amazon EMR
Example: Running Pig Scripts in Hue on Amazon EMR

Apache Spark on Amazon EMR
Example: Processing NY Taxi data using Spark on Amazon EMR

Amazon Redshift
Amazon Redshift and Big Data
Visualizing and Orchestrating Big Data
Example: Using TIBCO Spotfire to Visualize Data

Storage
MapReduce and HDFS/S3 From: http://sitestree.com/?p=10682
Categories:Big Data
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Post Data:2017-07-01 07:04:26

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Ambari Tools for Big Data #Big Data

HDFS
MapReduce2
YARN
Hive
HBase
Pig
Sqoop
Oozie
ZooKeeper
Flume
Ambari Metrics
BigInsights – Big R
BigInsights – BigSheets
BigInsights – Big SQL
BigInsights Data Server Manager
Kafka
Knox
R
Slider
Solr
Spark
BigInsights – Text Analytics
BigInsights Home From: http://sitestree.com/?p=10669
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Post Data:2017-06-23 14:17:33

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Some Big Data Terms #Big Data

MapReduce

MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel, distributed algorithm on a cluster.[1][2]

A MapReduce program is composed of a Map() procedure (method) that performs filtering and sorting (such as sorting students by first name into queues, one queue for each name) and a Reduce() method that performs a summary operation (such as counting the number of students in each queue, yielding name frequencies). The “MapReduce System” (also called “infrastructure” or “framework”) orchestrates the processing by marshalling the distributed servers, running the various tasks in parallel, managing all communications and data transfers between the various parts of the system, and providing for redundancy and fault tolerance.

Reference: https://en.wikipedia.org/wiki/MapReduce

 

Apache Pig

“is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.”

Reference: https://pig.apache.org/

 

Hive:

Hive provides a SQL-like interface to data stored in HDP.

Hive has three main functions: data summarization, query and analysis. It supports queries expressed in a language called HiveQL, which automatically translates SQL-like queries into MapReduce jobs executed on Hadoop. In addition, HiveQL supports custom MapReduce scripts to be plugged into queries.

Reference: http://searchdatamanagement.techtarget.com/definition/Apache-Hive

 

Flume:

Flume lets Hadoop users ingest high-volume streaming data into HDFS for storage. …. Integrating Data Silos with your Big Data Systems in Real-Time.

Reference: https://hortonworks.com/apache/flume/

 

SQoop:

Apache Sqoop efficiently transfers bulk data between Apache Hadoop and … Carolinas Healthcare: Using Big Data to Drive Point of Care Decision in Oncology.

https://hortonworks.com/apache/sqoop/

 

Oozie:

Apache Oozie is a Java Web application used to schedule Apache Hadoop jobs. …. Eight Big Data and Hadoop Meetups for the Hadoop Summit San Jose.

https://hortonworks.com/apache/oozie/

 

  From: http://sitestree.com/?p=10657
Categories:Big Data
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Post Data:2017-06-23 12:49:30

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Introduction to Scala : Learning Resources #Big Data

Creating a Scala Doc From: http://sitestree.com/?p=10655
Categories:Big Data
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Post Data:2017-07-01 08:00:13

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Spark and Machine Learning Resources #Big Data

What is Apache Spark: What is Spark SQL? What is RDD? What is Spark ML? What is GraphX
https://en.wikipedia.org/wiki/Apache_Spark (Sure theoreticians matter, SPark was first developed at the University of California, Berkeley’s AMPLab)

Tutorial: Apache Spark – RDD
https://www.tutorialspoint.com/apache_spark/apache_spark_rdd.htm

Hands-on Intro to Machine Learning with Apache Spark and Apache Zeppelin
https://www.youtube.com/watch?v=k4KOmnenuFk

Apache Spark Machine Learning Tutorial
https://mapr.com/blog/apache-spark-machine-learning-tutorial/

Why you should use Spark for machine learning
http://www.infoworld.com/article/3031690/analytics/why-you-should-use-spark-for-machine-learning.html

From: http://sitestree.com/?p=10620
Categories:Big Data
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Post Data:2017-06-18 11:49:20

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Step by Step Python and Django Installation #Blog

Step by Step Python and Django Installation

Check the video below. Also, search for related short notes on this site

 

Continue reading

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    Date Posted:2021-08-01 .Apply yourself, or submit others as candidates; Build a recruitment team to submit others as candidates; submit RFP to be considered for projects in future; Try to become a vendor so that you are asked to submit consultants/resources in future. If these work for you. This list is posted in this blog everyday provided there are new projects under the criteria

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      Date Posted:2021-07-31 .Apply yourself, or submit others as candidates; Build a recruitment team to submit others as candidates; submit RFP to be considered for projects in future; Try to become a vendor so that you are asked to submit consultants/resources in future. If these work for you. This list is posted in this blog everyday provided there are new projects under the criteria

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      2. Signal Smoke Marine, Orange (W8486-217390/A)
      3. communications-detection-and-fibre-optics-10031
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