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Posted on 25 October 2014 by Srinivas Nelakuditi

Java 8 Lambda Expressions Tutorial -6

Java 8 Lambda Feature can also be used to filter streams and also limit the number of records required from stream. In the below example.
We are creating a list of BankCheckingAccounts. We are depositing 1000 dollars into every account using lambdas. We are creating a balance filter and zip code filter.
We are printing only bank accounts with balance greater than 1000 and in zipcode 07034. We are also limiting for only 1 record to be provided as output.

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Posted on 25 October 2014 by Srinivas Nelakuditi

Java 8 Lambda Expressions Tutorial -5

Lambda Expressions is a very powerful feature available in JDK 8. Let us learn the technique of creating filters using lambdas and applying them on collections.
We can stream on a collection and apply multiple filters.

In the below example.
We are creating a list of BankCheckingAccounts. We are depositing 1000 dollars into every account using lambdas. We are creating a balance filter and zip code filter.
We are printing only bank accounts with balance greater than 1000 and in zipcode 07034.

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Posted on 25 October 2014 by Srinivas Nelakuditi

Java 8 Lambda Expressions Tutorial -4

Let us do another example to use lambda filtering in Java 8. Let us learn by example than by theory.

Given a list of bank accounts with firstname, lastname and account balance. Find all accounts with balance greater than 1000 dollars.

Filtering is a very power technique to filter. Objects required from a list or collections can be easily obtained.

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Posted on 25 October 2014 by Srinivas Nelakuditi

Java 8 Lambda Expressions Tutorial -3

Lambda is one of the most powerful feature added to java since 2005. Let us learn the power of lambda by example.
Let us create a class called BankCheckingAccount.java
Let us create a list of BankCheckingAccounts.
Each checking account has an initial balance of 100 dollars. Now deposit another 100 dollars into each account using lambda feature.

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Posted on 25 October 2014 by Srinivas Nelakuditi

Java 8 Lambda Expressions Tutorial -2

Lambda Basic Syntax:
(parameters) ->expression or (parameters) ->{ statements; }

Java 8 Lambda Expressions can be very effective when sorting collections.
Let us learn how to use Java Lambdas for Sorting Java Collections by Example:

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Posted on 25 October 2014 by Srinivas Nelakuditi

Java 8 Lambda Expressions Tutorial -1

Lambda expression feature is new in JDk8. This is one of the major feature added to java since Generics and Annotations in 2005.

Let us learn Lambda expressions in a series of learn by example tutorials:

Definition of Lambda Expression:

A major confusion with  Java anonymous class as an interface that contains only one method, then the syntax of anonymous classes may seem confusing and unclear. In these cases, you’re usually trying to pass functionality as an argument to another method, such as what action should be taken when someone clicks a button. Lambda expressions enable you to do this, to treat functionality as method argument, or code as data.

Example 1:

Example 2:
Using Lambdas for Java Runnable

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Posted on 18 October 2014 by Srinivas Nelakuditi

Install Apache Storm for Development

Step 1: Boot up your Ubuntu virtual machine using Oracle Virtual Box

Step 2: Install JDK 7 or JDK 8 and set JAVA_HOME

Step 3: Install Maven2

Step 4: Download Storm

use tar -xvzf apache-storm-0.9.3-rc1.tar.gz

Your environment is now ready for running your storm projects.

In the next blog we will to code for storm and learn the basics.

 

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Posted on 12 October 2014 by Srinivas Nelakuditi

Guarantees from Apache Storm

Apache Storm provides guarantees and new possibilities which could not achieved with Hadoop and other batch oriented data processing engines.

Apache Strom provides real-time computation and facilitates real-time feedback for any data. Storm helps in parallel real-time processing of data.

Key Guarantees of Storm:

  • Broad Set of Use Cases: Apache Storm can process streams of data or messages and update databases or push data into hadoop for further analysis.
  • Scalable: Storm can process billions of messages per second by using the massive cluster features. A 100 node cluster can process 1,00,000,000 messages per second. Storm uses Zookeeper for cluster management and scalability.
  • Guarantees no data loss: Storm guarantees 100% data processing and no data loss.
  • Extremely robust: Storm clusters are robust to maintain when compared to a hadoop cluster.
  • Fault-tolerant: If there are errors during computation, storm will auto reassign the tasks.
  • Programming language agnostic: Storm is platform independent and programming in storm is supported by multiple platforms.

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Posted on 12 October 2014 by Srinivas Nelakuditi

Apache Storm Introduction

Apache Storm is a massive data crunching distributed real-time computation engine. Apache Storm can be defined as hadoop for realtime. Apache Storm processes data in real time where as Hadoop processes data in batch oriented fashion.

Apache Storm is Open Source project. We at Vulab use Storm in our large fortune 500 projects and clients in their big data initiatives. Vulab provides hands-on training on Java, JEE, Apache Storm, Apache Hadoop, Apache Spark, Kafka and Hadoop using Open Source 100% Apache Hadoop, Hortonworks Hadoop, MapR Hadoop or Cloudera Hadoop.

Storm is fun and easy to use. Let us run through a series of of training sessions to master Apache Storm.

Use Cases of Apache Storm:

Apache Storm has many use cases in the big data market today: Storm is used for real-time analytics calculation and display, online machine learning, continuous computation needs, distributed RPC and communication protocols discovery, ETL and monitoring, and more…..

Apache Storm at Groupon.com:

Storm is being used at Groupon to build real-time data integration systems. Storm allows for normalizing data points with high throughput and low latency for large data loads.

Apache Storm at Twitter.com:

Publishers performance at twitter is measured using Apache Storm. Every tweet generated and every click on a tweet and a retweet are measured using storm. Apach storm is also being used for spam detection, revenue optimization and content discovery at twitter. More projects are currently being migrated to Storm because of its ease of use, faster development and testing cycles and powerful integration with third party databases and systems.

Apache Storm for Navisite Event Log Monitoring:

Navisite is using Storm to process up to 50k messages per second. Real time intrusion detection is being done using  Storm at Navisite. Navisite has tried different computation engines and has chosen Apache Storm after heavy testing with real time data.

There are too many use cases to list here. Please search on Google to get the most current use cases of Apache Storm.

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Posted on 11 October 2014 by Srinivas Nelakuditi

Apache Kafka Tutorial Series

Apache Kafka Tutorials 

Apache Kafka is the industry leading open source distributed messaging platform. Kafka provides the following:

  • Persistent messaging to hard-disk with O(1) disk structures that provide constant time performance even with many TB of stored messages.
  • High-throughput: Just with simple modest hardware Kafka can support hundreds of thousands of messages per second.
  • Explicit support for partitioning messages over Kafka servers and distributing consumption over a cluster of consumer machines while maintaining per-partition ordering semantics.
  • Support for parallel data load into Hadoop HDFS.

TUTORIAL LINKS

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