TIPS, TRICKS, AND SOLUTIONS FOR USING SPARK IN PRODUCTION

Spark's popularity means the field is expanding?in terms of both use and capability. Faster than Hadoop and MapReduce, but compatible with Java^®, Scala, Python^®, and R, this open source clustering framework is becoming a must-have skill. Spark: Big Data Cluster Computing in Production goes beyond the basics to show you how to bring Spark to real-world production environments. With expert instruction, real-life use cases, and frank discussion, this guide helps you move past the challenges and bring proof-of-concept Spark applications live.

• Fine-tune your Spark app to run on production data
• Manage resources, organize storage, and master monitoring
• Learn about potential problems from real-world use cases, and see where Spark fits best
• Estimate cluster size and nail down hardware requirements
• Tune up performance with memory management, partitioning, shuffling, and more
• Ensure data security with Kerberos
• Head off Spark streaming problems in production
• Integrate Spark with Yarn, Mesos, Tachyon, and more