mapreduce-tutorial.blogspot.com

MapReduce Tutorial

Using Amazon Web Services. Hadoop's power comes from its ability to perform work on a large number of machines simultaneously. What if you want to experiment with Hadoop, but do not have many machines? While operations on a two or four-node cluster are functionally equivalent to those on a 40 or 100-node cluster, processing larger volumes of data will require a larger number of nodes. After the cluster has been started, you can log in to the head node over ssh with the bin/hadoop-ec2 login script, and pe...

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Using Amazon Web Services. Hadoop's power comes from its ability to perform work on a large number of machines simultaneously. What if you want to experiment with Hadoop, but do not have many machines? While operations on a two or four-node cluster are functionally equivalent to those on a 40 or 100-node cluster, processing larger volumes of data will require a larger number of nodes. After the cluster has been started, you can log in to the head node over ssh with the bin/hadoop-ec2 login script, and pe...

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MapReduce Tutorial | mapreduce-tutorial.blogspot.com Reviews

https://mapreduce-tutorial.blogspot.com

Using Amazon Web Services. Hadoop's power comes from its ability to perform work on a large number of machines simultaneously. What if you want to experiment with Hadoop, but do not have many machines? While operations on a two or four-node cluster are functionally equivalent to those on a 40 or 100-node cluster, processing larger volumes of data will require a larger number of nodes. After the cluster has been started, you can log in to the head node over ssh with the bin/hadoop-ec2 login script, and pe...

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mapreduce-tutorial.blogspot.com

1

MapReduce Tutorial: Reporting Custom Metrics

http://mapreduce-tutorial.blogspot.com/2011/04/reporting-custom-metrics.html

The Reporter object passed in to your Mapper and Reducer classes can be used to update counters. The same set of counter variables can be contributed to by all Mapper and Reducer instances across your cluster. The values are aggregated by the master node of the cluster, so they are "thread-safe" in this manner. Public class MyMapper extends MapReduceBase implements. Static enum RecordCounters { TYPE A, TYPE B, TYPE UNKNOWN };. Public boolean isTypeARecord(Text input) { . }. Else if (isTypeBRecord(key) {.

2

MapReduce Tutorial: Distributing Debug Scripts

http://mapreduce-tutorial.blogspot.com/2011/04/distributing-debug-scripts.html

These scripts will be run on whichever node encounters failing tasks. You can use these scripts to perform automation to allow you to more easily inspect only the failing tasks: e.g., email the stdout/stderr to an administrator email address; upload the failed task's log files to a common NFS-mounted "debug dump" directory, preserve local state modifications made by map tasks, etc. Private static final String FAILED MAP SCRIPT NAME = "map-fail";. Private static final String HDFS SCRIPT DIR = "/debug";.

3

MapReduce Tutorial: Custom Data Types

http://mapreduce-tutorial.blogspot.com/2011/04/custom-data-types.html

Hadoop MapReduce uses typed data at all times when it interacts with user-provided Mappers and Reducers: data read from files into Mappers, emitted by mappers to reducers, and emitted by reducers into output files is all stored in Java objects. The key can be represented as a Text object, but what about the value? How do we build a Point3D class which Hadoop can transmit? The answer is to implement the Writable interface, which requires two methods:. Public interface Writable {. Public float x;. In Hadoo...

4

MapReduce Tutorial: MapReduce Basics

http://mapreduce-tutorial.blogspot.com/2011/04/mapreduce-basics.html

MapReduce programs are designed to compute large volumes of data in a parallel fashion. This requires dividing the workload across a large number of machines. This model would not scale to large clusters (hundreds or thousands of nodes) if the components were allowed to share data arbitrarily. The communication overhead required to keep the data on the nodes synchronized at all times would prevent the system from performing reliably or efficiently at large scale. The first phase of a MapReduce program is...

5

MapReduce Tutorial: MapReduce Introduction

http://mapreduce-tutorial.blogspot.com/2011/04/mapreduce-introduction.html

MapReduce is a programming model designed for processing large volumes of data in parallel by dividing the work into a set of independent tasks. MapReduce programs are written in a particular style influenced by functional programming constructs, specifically idioms for processing lists of data. This blog explains the nature of this programming model and how it can be used to write programs which run in the Hadoop environment. Using Amazon Web Services. Distributing Auxiliary Job Data.

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oracle-datawarehousing.blogspot.com

Compare OLTP and Data Warehousing Environments ~ ORACLE DATAWAREHOUSE

http://oracle-datawarehousing.blogspot.com/2011/02/compare-oltp-and-data-warehousing.html

All about Data Warehousing with Oracle. Error Logging and Handling. Compare OLTP and Data Warehousing Environments. Following figure shows the key differences between OLAP and DataWarehousing Environments. One major difference between the types of system is that data warehouses are not. Usually in third normal form (3NF), a type of data normalization common in OLTP. Data warehouses and OLTP systems have very different requirements. Here are some. 9632; Data modifications. 9632; Schema design. OLTP system...

oracle-datawarehousing.blogspot.com

Data Warehouse Architectures ~ ORACLE DATAWAREHOUSE

http://oracle-datawarehousing.blogspot.com/2011/02/data-warehouse-architectures.html

All about Data Warehousing with Oracle. Error Logging and Handling. Data warehouses and their architectures vary depending upon the specifics of an. Organization's situation. Three common architectures are:. 9632; Data Warehouse Architecture (Basic). 9632; Data Warehouse Architecture (with a Staging Area). 9632; Data Warehouse Architecture (with a Staging Area and Data Marts). Data Warehouse Architecture (Basic). Warehouses because they pre-compute long operations in advance. For example, a. Your warehou...

qlikview-tutorials.blogspot.com

QlikView Tutorials: QlikView Introduction

http://qlikview-tutorials.blogspot.com/2011/07/qlikview-introduction.html

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QlikView Tutorials: Working with QlikView Part1

http://qlikview-tutorials.blogspot.com/2011/07/working-with-qlikview-part1.html

Working with QlikView Part1. Working with qlik view part 1. Awesome Inc. template. Powered by Blogger.

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QlikView Tutorials: QlikView- Advanced Features

http://qlikview-tutorials.blogspot.com/2011/07/qlikview-advanced-features.html

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QlikView Tutorials: Working with QlikView Part2

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Working with QlikView Part2. Working with qlik view part 2. Awesome Inc. template. Powered by Blogger.

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QlikView Tutorials: QlikView Overview

http://qlikview-tutorials.blogspot.com/2011/10/qlikview-overview.html

QlikView is an In-memory. In-memory is important for performance, but it takes a lot more to deliver a Business Discovery platform. Traditional BI based on queries and cubes may run in memory for faster response time, but they still require IT to manually maintain the data associations users depend on. It’s what QlikView does with in-memory technology that really makes a difference. The QlikView Business Discovery platform:. 2)Calculates aggregations on the fly, as needed, for a super-fast user experience.

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WebFOCUS TUTORIALS: WebFOCUS InfoAssist User’s Manual

http://webfocus-tutorials.blogspot.com/2009/11/webfocus-infoassist-users-manual.html

Best online resource for WebFOCUS Tutorial Tutorials. At Tutorial Blogs we value your opinion - Please Respond- Click Here. WebFOCUS Reporting Server Installation. Developer Studio Installation and Configuration. WebFOCUS Managed Reporting Developer's Manual. WebFOCUS Desktop Error Messages. WebFOCUS Security and Administration. Using WebFOCUS Visual Discovery Components. WebFOCUS InfoAssist User's Manual. Describing Data with Graphical Tools. Developing Reporting Applications with Graphical Tools.

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WebFOCUS TUTORIALS: WebFOCUS Jobs

http://webfocus-tutorials.blogspot.com/2009/11/webfocus-jobs.html

Best online resource for WebFOCUS Tutorial Tutorials. At Tutorial Blogs we value your opinion - Please Respond- Click Here. WebFOCUS Reporting Server Installation. Developer Studio Installation and Configuration. WebFOCUS Managed Reporting Developer's Manual. WebFOCUS Desktop Error Messages. WebFOCUS Security and Administration. Using WebFOCUS Visual Discovery Components. WebFOCUS InfoAssist User's Manual. Describing Data with Graphical Tools. Developing Reporting Applications with Graphical Tools.

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WebFOCUS TUTORIALS: WebFOCUS Best Practices

http://webfocus-tutorials.blogspot.com/2009/11/webfocus-best-practices.html

Best online resource for WebFOCUS Tutorial Tutorials. At Tutorial Blogs we value your opinion - Please Respond- Click Here. WebFOCUS Reporting Server Installation. Developer Studio Installation and Configuration. WebFOCUS Managed Reporting Developer's Manual. WebFOCUS Desktop Error Messages. WebFOCUS Security and Administration. Using WebFOCUS Visual Discovery Components. WebFOCUS InfoAssist User's Manual. Describing Data with Graphical Tools. Developing Reporting Applications with Graphical Tools. There...

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mapreduce-tutorial.blogspot.com

MapReduce Tutorial

Using Amazon Web Services. Hadoop's power comes from its ability to perform work on a large number of machines simultaneously. What if you want to experiment with Hadoop, but do not have many machines? While operations on a two or four-node cluster are functionally equivalent to those on a 40 or 100-node cluster, processing larger volumes of data will require a larger number of nodes. After the cluster has been started, you can log in to the head node over ssh with the bin/hadoop-ec2 login script, and pe...

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The Apache Way | Open Source Community

The Apache Way: Hadoop resources. A resource for those seeking open source enlightenment. The Apache Software Foundation. What is Apache Hadoop? The hottest new data processing tool since. the abacus. The best resource for learning about Apache Hadoop is the project website. There are more resources to find, both within the website and on the Hadoop mailing list archives. An excellent reference to The Apache Way is JAaron Farr's most excellent presentation entitled " The Apache Way. Happy Birthday, ASF.

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mapreduce.sandia.gov

MapReduce-MPI Library

A grain of wisdom is worth an ounce of knowledge, which is worth a ton of data. It is a capital mistake to theorize before one has data. This is the home page for the MapReduce-MPI (MR-MPI) library, which is an open-source implementation of MapReduce written for distributed-memory parallel machines on top of standard MPI message passing. Latest features and bug fixes. The MR-MPI library was developed at Sandia National Laboratories, a US Department of Energy facility, for use on informatics problems.