apache.org	Apache Spark Official Notes White paper on Spark Spark standalone mode Spark cluster mode Spark on Yarn Spark Tuning Dynamic Resource Allocation Spark Streaming Resilient Distributed Datasets (RDDs) External Datasets RDD Operations Understanding closures Broadcast Variables Accumulators Working with Key-Value Pairs
cloudera.com	Apache Spark key concepts from Cloudera Tune Spark Jobs
databricks.com	Apache Spark key concepts from Databricks Window functions Project Tungsten Spark reference applications Gitbook Spark apps reference Gitbook Spark tuning
databricks.com	Sorting a petabyte using Spark
wordpress.com	Apache Spark resources
mapr.com beekeeperdata.com github.com github.com	Spark examples The 5-Minute Guide to Understanding the Significance of Apache Spark
0x0fff.com 0x0fff.com	Spark architecture
mit.edu madhukaraphatak.com hortenworks.com slideshare.net	Spark Catalyst Optimizor
spark.apache.org fastutil.di.unimi.it	Spark tuning and usage of fastutil collections
dzone.com	SBT Setup for Scala 2.10 and Spark
stackoverflow.com	Spark RDD method 'collect' is necessary before calling 'foreach' etc Method 'collect' is used to bring data back to driver program, before doing any data operation
stackoverflow.com	Spark: using singleton instance of the SQLContext before: import sqlContext.implicits._
stackoverflow.com github.com	Spark: sum of row values
github.com apache.org	Spark: streaming guide and examples
gitbook.com	Spark: best practices and tuning
github.com	Spark: Qubole Sparklens tool for performance tuning Spark
github.com	Spark: Data Lineage Tracking and Visualization tool
stackoverflow.com stackoverflow.com tutorialspoint.com	Creating Spark DataFrame using StructType/StructField or Simple Objects
apache.org stackoverflow.com databricks.com	Apache Spark has three types of API RDD: many transformation methods, such as map(), filter(), and reduce() DataFrame: part of the Project Tungsten, to improve the performance Dataset: extension to DataFrames, provides an object-oriented interface