Tuesday, 6 May 2014
Monday, 21 April 2014
Apache Oozie High Availability: Apache Oozie High Availability
Apache Oozie High Availability: Apache Oozie High Availability: Apache Oozie is a great tool for building workflows of Hadoop jobs and scheduling them repeatedly. However, the user experience c...
Thursday, 26 December 2013
Hadoop Training - HadoopUniversity.IN
Hadoop Training in Chennai
Training Overview:
Our five-day Hadoop Training for Architect course is a highly interactive and educational tour de force that will provide students with the essential building blocks to build reliable and scalable data processing systems using the Apache Hadoop open-source software. Students will learn through lecture, discussion and hands on exercises. At the end of the course students will:
- Have a solid understanding of the Hadoop ecosystem of products
- Demonstrate proficiency in writing MapReduce code
- Learn how to leverage HBase to store and retrive data
- Understand best practices for developing and debugging Hadoop solutions
- Practice and understand other Apache projects such as Hive, Pig, Oozie, and Sqoop
- Understand more advanced Hadoop and Hadoop API topics that are commonly encountered
- Capable of working on proof of concept projects
Students completing the course will be provided the opportunity to take up the POC Project sponsored by HadoopUniversity.IN
Training Overview:
Our five-day Hadoop Training for Architect course is a highly interactive and educational tour de force that will provide students with the essential building blocks to build reliable and scalable data processing systems using the Apache Hadoop open-source software. Students will learn through lecture, discussion and hands on exercises. At the end of the course students will:
- Have a solid understanding of the Hadoop ecosystem of products
- Demonstrate proficiency in writing MapReduce code
- Learn how to leverage HBase to store and retrive data
- Understand best practices for developing and debugging Hadoop solutions
- Practice and understand other Apache projects such as Hive, Pig, Oozie, and Sqoop
- Understand more advanced Hadoop and Hadoop API topics that are commonly encountered
- Capable of working on proof of concept projects
Students completing the course will be provided the opportunity to take up the POC Project sponsored by HadoopUniversity.IN
Thursday, 12 December 2013
Cassandra Certification Training and Consulting Services: High Paying Jobs for the Future of Big Data
Cassandra Certification Training and Consulting Services: High Paying Jobs for the Future of Big Data: Big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing...
High Paying Jobs for the Future of Big Data
Big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis.
IBM reports that "90% of the data in the world today has been created in the last two years alone." Every interaction from a Facebook "like" to a Google search or click on a headline from Yahoo! lends to some small stored bit of information. But beyond what we do on the Internet, there is the data generated from traffic sensors, sales figures at small businesses, and the immense amount of data utilized in hospitals about patients to help patients.
The most amazing test refered to by the administrators reviewed by The Wall Street Journal about huge information was "confirming how to get esteem from the information," and the best way to do that is through individuals, and laborers in these seven profession fields are the ones ready to profit the most from this information renaissance.
IBM reports that "90% of the data in the world today has been created in the last two years alone." Every interaction from a Facebook "like" to a Google search or click on a headline from Yahoo! lends to some small stored bit of information. But beyond what we do on the Internet, there is the data generated from traffic sensors, sales figures at small businesses, and the immense amount of data utilized in hospitals about patients to help patients.
The most amazing test refered to by the administrators reviewed by The Wall Street Journal about huge information was "confirming how to get esteem from the information," and the best way to do that is through individuals, and laborers in these seven profession fields are the ones ready to profit the most from this information renaissance.
7 High-Paying Jobs
Software Developer
Market Research Analysts
Post-secondary Teacher
Database Administrators
Computer System Analyst
Information Security Analysts, Web Developers, and Computer network Architects
Network and Computer System Administrators
Software Developer
Surely software developers - the individuals who make and compose Pc programs - aren't only included in Big Data, but with each passing day, more people are needed to make the programs that can effectively and effortless collect, synthesize, and process all of the data created. For college graduates with degrees in fields like Pc science, programming designing, arithmetic, or some other identified field, what's to come for engineers was splendid 10 years back, and that remains accurate today.
Market Research Analysts
Market research analysts are going to be the ones who work in almost every industry who view the massive amounts of data that is collected and then report on their findings.
Since they can work in a variety of fields, from consumer product companies, manufacturing firms, or even banks, there is a lot of demand for the people who can make decisions based on all the data that is collected. A career as a market research analyst is best prepared for with a degree in statistics or math, with coursework in communications or other social sciences.
Post-secondary Teacher
postsecondary teachers will be in high demand as a result of big data. There will be more and more students who pursue careers in big data , and as a result, there will be a need for people who are prepared, capable, and willing to teach them the required skills they need to succeed.
Database Administrators
It is completely vital to have individuals breaking down the information - yet provided that they don't have secure and sound information to dissect, they'll settle on wrong choices. Database managers are the ones who utilize the programming and devices made by the engineers to store and arrange the information that will be utilized by statistical surveying and different investigators. While a degree in any machine identified field can set somebody on the way to turning into a database head, one in administration data frameworks (Mis) is frequently the best fit.
Computer System Analyst
Computer systems analysts are often the intermediaries between a corporation's IT department and its business departments. As big data progresses, computer systems analysts are an essential cog to help a business understand its current computer systems and make recommendations for expanded systems and processes to meet the ever-evolving world of big data.
Information Security Analysts, Web Developers, and Computer network Architects
Information security analysts ensure data is safe and secure, web developers create websites that attempt to capture the best practices wielded from big data, and network architects ensure that data and information flows seamlessly.
Network and Computer System Administrators
With the vast amount of information collected, both internal and external computer networks will be under increased demand and strain, and there will be a high demand for the people who can ensure things continue without a hitch. Often a degree in computer or information sciences is a key point of entry, but a degree in an engineering field (whether it be computer or electrical) can also be immensely helpful.
Thursday, 8 August 2013
Hadoop Hbase Training in Chennai
What is HBase?
Apache HBase is the Hadoop database, a distributed, scalable, big data store.
Use Apache HBase when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. Apache HBase is an open-source, distributed, versioned, column-oriented store modeled.
Features
Linear and modular scalability.
Strictly consistent reads and writes.
Automatic and configurable sharding of tables
Automatic failover support between RegionServers.
Convenient base classes for backing Hadoop MapReduce jobs with Apache HBase tables.
Easy to use Java API for client access.
Block cache and Bloom Filters for real-time queries.
Query predicate push down via server side Filters
Thrift gateway and a REST-ful Web service that supports XML, Protobuf, and binary data encoding options
Extensible jruby-based (JIRB) shell
Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX
Hadoop Training Chennai - Learn From Technical Architects & Consultants
Big Data will drive the industrial Internet
"The world is on the threshold of a new era of innovation and change with the rise of the industrial Internet"
BigDataTraining.IN - India's Leading BigData Consulting & Training Provider, Request a Quote!
Hadoop & Big Data Training | Development | Consulting | Projects
http://www.bigdatatraining.in/hadoop-training-chennai/
http://www.hadooptrainingchennai.in/hadoop-training-in-chennai/
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info@bigdatatraining.in
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044 - 42645495
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Wednesday, 31 July 2013
Apache Cassandra Training @ BigDataTraining.IN
Apache Cassandra
Key improvements
Cassandra Query Language (CQL) Enhancements
One of the main objectives of Cassandra 1.1 was to bring CQL up to parity with the legacy API and command line interface (CLI) that has shipped with Cassandra for several years. This release achieves that goal. CQL is now the primary interface into the DBMS.
Composite Primary Key Columns
The most significant enhancement of CQL is support for composite primary key columns and wide rows. Composite keys distribute column family data among the nodes. New querying capabilities are a beneficial side effect of wide-row support. You use an ORDER BY clause to sort the result set.
Global Row and Key Caches
Memory caches for column families are now managed globally instead of at the individual column family level, simpliying configuration and tuning. Cassandra automatically distributes memory for various column families based on the overall workload and specific column family usage. Administrators can choose to include or exclude column families from being cached via the caching parameter that is used when creating or modifying column families.
Row-Level Isolation
Full row-level isolation is now in place so that writes to a row are isolated to the client performing the write and are not visible to any other user until they are complete. From a transactional ACID (atomic, consistent, isolated, durable) standpoint, this enhancement now gives Cassandra transactional AID support. Consistency in the ACID sense typically involves referential integrity with foreign keys among related tables, which Cassandra does not have. Cassandra offers tunable consistency not in the ACID sense, but in the CAP theorem sense where data is made consistent across all the nodes in a distributed database cluster. A user can pick and choose on a per operation basis how many nodes must receive a DML command or respond to a SELECT query.
Hadoop Integration
The following low-level features have been added to Cassandra’s support for Hadoop:
Basic architecture
A Cassandra instance is a collection of independent nodes that are configured together into a cluster. In a Cassandra cluster, all nodes are peers, meaning there is no master node or centralized management process. A node joins a Cassandra cluster based on certain aspects of its configuration. This section explains those aspects of the Cassandra cluster architecture.
Cassandra uses a protocol called gossip to discover location and state information about the other nodes participating in a Cassandra cluster. Gossip is a peer-to-peer communication protocol in which nodes periodically exchange state information about themselves and about other nodes they know about.
In Cassandra, the gossip process runs every second and exchanges state messages with up to three other nodes in the cluster. The nodes exchange information about themselves and about the other nodes that they have gossiped about, so all nodes quickly learn about all other nodes in the cluster. A gossip message has a version associated with it, so that during a gossip exchange, older information is overwritten with the most current state for a particular node.
When a node first starts up, it looks at its configuration file to determine the name of the Cassandra cluster it belongs to and which node(s), called seeds, to contact to obtain information about the other nodes in the cluster. These cluster contact points are configured in the cassandra.yaml configuration file for a node.
Failure detection is a method for locally determining, from gossip state, if another node in the system is up or down. Failure detection information is also used by Cassandra to avoid routing client requests to unreachable nodes whenever possible.
BigDataTraining.IN has a strong focus and established thought leadership in the area of Big Data and Analytics. We use a global delivery model to help you to evaluate and implement solutions tailored to your specific technical and business context.
http://www.bigdatatraining.in/hadoop-development/training-schedule/
http://www.bigdatatraining.in/contact/
Mail:
info@bigdatatraining.in
Call:
+91 9789968765
044 - 42645495
Visit Us:
#67, 2nd Floor, Gandhi Nagar 1st Main Road, Adyar, Chennai - 20
[Opp to Adyar Lifestyle Super Market]
Key improvements
Cassandra Query Language (CQL) Enhancements
One of the main objectives of Cassandra 1.1 was to bring CQL up to parity with the legacy API and command line interface (CLI) that has shipped with Cassandra for several years. This release achieves that goal. CQL is now the primary interface into the DBMS.
Composite Primary Key Columns
The most significant enhancement of CQL is support for composite primary key columns and wide rows. Composite keys distribute column family data among the nodes. New querying capabilities are a beneficial side effect of wide-row support. You use an ORDER BY clause to sort the result set.
Global Row and Key Caches
Memory caches for column families are now managed globally instead of at the individual column family level, simpliying configuration and tuning. Cassandra automatically distributes memory for various column families based on the overall workload and specific column family usage. Administrators can choose to include or exclude column families from being cached via the caching parameter that is used when creating or modifying column families.
Row-Level Isolation
Full row-level isolation is now in place so that writes to a row are isolated to the client performing the write and are not visible to any other user until they are complete. From a transactional ACID (atomic, consistent, isolated, durable) standpoint, this enhancement now gives Cassandra transactional AID support. Consistency in the ACID sense typically involves referential integrity with foreign keys among related tables, which Cassandra does not have. Cassandra offers tunable consistency not in the ACID sense, but in the CAP theorem sense where data is made consistent across all the nodes in a distributed database cluster. A user can pick and choose on a per operation basis how many nodes must receive a DML command or respond to a SELECT query.
Hadoop Integration
The following low-level features have been added to Cassandra’s support for Hadoop:
- Secondary index support for the column family input format. Hadoop jobs can now make use of Cassandra secondary indexes.
- Wide row support. Previously, wide rows that had, for example, millions of columns could not be accessed, but now they can be read and paged through in Hadoop.
- The bulk output format provides a more efficient way to load data into Cassandra from a Hadoop job.
Basic architecture
A Cassandra instance is a collection of independent nodes that are configured together into a cluster. In a Cassandra cluster, all nodes are peers, meaning there is no master node or centralized management process. A node joins a Cassandra cluster based on certain aspects of its configuration. This section explains those aspects of the Cassandra cluster architecture.
Cassandra uses a protocol called gossip to discover location and state information about the other nodes participating in a Cassandra cluster. Gossip is a peer-to-peer communication protocol in which nodes periodically exchange state information about themselves and about other nodes they know about.
In Cassandra, the gossip process runs every second and exchanges state messages with up to three other nodes in the cluster. The nodes exchange information about themselves and about the other nodes that they have gossiped about, so all nodes quickly learn about all other nodes in the cluster. A gossip message has a version associated with it, so that during a gossip exchange, older information is overwritten with the most current state for a particular node.
When a node first starts up, it looks at its configuration file to determine the name of the Cassandra cluster it belongs to and which node(s), called seeds, to contact to obtain information about the other nodes in the cluster. These cluster contact points are configured in the cassandra.yaml configuration file for a node.
Failure detection is a method for locally determining, from gossip state, if another node in the system is up or down. Failure detection information is also used by Cassandra to avoid routing client requests to unreachable nodes whenever possible.
BigDataTraining.IN has a strong focus and established thought leadership in the area of Big Data and Analytics. We use a global delivery model to help you to evaluate and implement solutions tailored to your specific technical and business context.
http://www.bigdatatraining.in/hadoop-development/training-schedule/
http://www.bigdatatraining.in/contact/
Mail:
info@bigdatatraining.in
Call:
+91 9789968765
044 - 42645495
Visit Us:
#67, 2nd Floor, Gandhi Nagar 1st Main Road, Adyar, Chennai - 20
[Opp to Adyar Lifestyle Super Market]
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