Rajesh Reddy Kundur

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• 10 Years of experience in Information Technology in system architecture, application design, application development, data analysis, analytics solution design and consulting experience. • Over 5 years of experience in developing and delivering real world Big Data/Hadoop solutions. • Expertise in building scalable analytics solutions using Cloudera distributions of Hadoop, Apache Spark, MapReduce, Apache Crunch, Apache Solr, Pig, Hive, HBase and Cassandra. • Expertise in creating efficient, portable, fast & compact big data models using Google Protocol Buffers, Avro, Thrift and Apache Parquet for Big Data Analytics Applications. • Extensively worked in Continuous Integration and Continu...

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Rajesh Reddy Kundur

Tuning Apache Spark for Large-Scale Workloads Gaoxiang Liu and Sital Kedia

Hive + Tez: A Performance Deep Dive

Real Time Analytics: Algorithms and Systems

Why Your Apache Spark Job is Failing

VISIONS OF THE FUTURE Little Rock 2016

Hive join optimizations

Apache Storm vs. Spark Streaming – two Stream Processing Platforms compared

Apache storm vs. Spark Streaming

10 Steps great leaders take when things go wrong

Building a modern Application with DataFrames

Building a Turbo-fast Data Warehousing Platform with Databricks

Introducing DataFrames in Spark for Large Scale Data Science

Simplifying Big Data Analytics with Apache Spark

Strata NYC 2015: Sketching Big Data with Spark: randomized algorithms for large-scale data analytics

Apache® Spark™ 1.5 presented by Databricks co-founder Patrick Wendell

Dynamic Allocation in Spark

Spark DataFrames: Simple and Fast Analytics on Structured Data at Spark Summit 2015

Apache Kafka 0.8 basic training - Verisign

2013 July 23 Toronto Hadoop User Group Hive Tuning

Data Source API in Spark