spark data lineage

needs of the business. Figure 2 shows the entire process of the spark streaming. Figure 2 Spark streaming architecture diagram Fault tolerance : Fault tolerance is critical for streaming computing. First we need to clarify the fault tolerance mechanism of the RDD in Spark. Each RDD is an immutable distributed, reconfigurable

Label:This article explains the structured data processing of spark, including: Spark SQL, DataFrame, DataSet, and Spark SQL services. This article focuses on the structured data processing of the spark 1.6.x, but because of the r

The data flow of an iterative machine learning algorithm in spark can be understood by graph 2.3来. Compare it to the iterative machine learning data stream of Hadoop Mr in figure 2.1. You'll find in HadoopEach iteration of MR involves the reading and writing of HDFs, which is much simpler in spark. It only requires one

. For a memory-based computing framework like SPARK, the GC problem is particularly prominent, it will cache a large amount of data in the JVM heap space, which is the data to be used in the calculation, the GC can not be removed, every time the full GC will do a global scan of the data, This is time consuming, and as

Liaoliang Teacher's course: The 2016 big Data spark "mushroom cloud" action spark streaming consumption flume collected Kafka data DIRECTF way job.First, the basic backgroundSpark-streaming get Kafka data in two ways receiver and direct way, this article describes the way of

Recently, after listening to Liaoliang's 2016 Big Data spark "mushroom cloud" action, Flume,kafka and spark streaming need to be integrated.Feel a moment difficult to get started, or start from the simple: my idea is that, flume produce data, and then output to spark streami

Teach you how to be a master of spark big Data? Spark is now being used by more and more businesses, like Hadoop, where Spark is also submitting tasks to the cluster as a job, so how do you become a master of spark big Data? Here'

Spark is a cluster computing platform originating from the University of California, Berkeley, amplab. It is based on memory computing and has hundreds of times better performance than hadoop. It starts from multi-iteration batch processing, it is a rare and versatile player that combines multiple computing paradigms, such as data warehouses, stream processing, and graph computing.

Tags: save overwrite worker ASE body compatible form result printWelcome to the big Data and AI technical articles released by the public number: Qing Research Academy, where you can learn the night white (author's pen name) carefully organized notes, let us make a little progress every day, so that excellent become a habit!One, spark SQL: Similar to Hive, is a data