Apache Spark is becoming very popular among organization looking to leverage its fast, in-memory computing capability for big-data processing. This article is for beginners to get started with Spark Setup on Eclipse/Scala IDE and getting familiar with Spark terminologies in general –
Hope you have read previous article on RDD basics , to get a basic understanding of Spark RDD.
Tools Used :
Scala IDE for Eclipse – Download latest version of Scala IDE from here .Here, I used Scala IDE 4.7.0 Release, which support both Scala and Java
Scala Version – 2.11 ( make sure scala compiler is set to this version as well)
I am writing this post to announce the general availability of my book on ELK stack titled ” Learning ELK Stack ” with PacktPub publications.
Book aims to provide individuals/technologists who seek to implement their own log and data analytics solutions using opensource stack of Elasticsearch, Logstash and Kibana popularly known as ELK stack.
This is the first book ever published which covers ELK stack.
Apache HCatalog is a Storage Management Layer for Hadoop that helps to users of different data processing tools in Hadoop ecosystem like Hive, Pig and MapReduce easily read and write data from the cluster.HCatalog enables with relational view of data from RCFile format, Parquet, ORC files, Sequence files stored on HDFS. It also exposes REST API exposed to external systems to access the metadata. (more…)
Until Java 7, java.util.Hashmap implementations always suffered with the problem of Hash Collision, i.e. when multiple hashCode() values end up in the same bucket, values are placed in a Linked List implementation, which reduces Hashmap performance from O(1) to O(n).
Improve the performance of java.util.HashMap under high hash-collision conditions by using balanced trees rather than linked lists to store map entries.This will improve collision performance for any key type that implements Comparable. (more…)
Simple String Example for Setting up Camus for Kafka-HDFS Data Pipeline
I came across Camus while building a Lambda Architecture framework recently. I couldn’t find a good Illustration of getting started with Kafk-HDFS pipeline , In this post we will see how we can use Camus to build a Kafka-HDFS data pipeline using a twitter stream produced by Kafka Producer as mentioned in last post .
What is Camus?
Camus is LinkedIn’s Kafka->HDFS pipeline. It is a mapreduce job that does distributed data loads out of Kafka. It includes the following features: (more…)
Twitter opensourced it’s Hosebird client (hbc) , a robust Java HTTP library for consuming Twitter’s Streaming API . In this post, I am going to present a demo of how we can use hbc to create a Kafka twitter stream producer , which tracks few terms on twitter statuses and produces a kafka stream out of it, which can be utilized later for counting the terms, or putting that data from Kafka to Storm (Kafka-Storm pipeline ) or HDFS ( as we will see in next post for using Camus API ).