Learn spark technology, adapt to big data development trend

At present, real-time computing, analysis and visualization of big data is the key to the real application of big data in industry. To meet this need and trend, open source organization Apache proposes a framework based on the spark analysis and computation, with the advantages of:

(1) Superior performance. Spark Technology in the framework refers to in-memory computing: Data processing runs only in system memory, avoiding the time consuming of frequent data exchange between hard disks and memory in the previous frame system. In addition, the Spark framework provides a unified data processing platform for batch processing (spark Core), interactive (spark SQL), streaming (spark streaming), machine learning (MLlib), and Graph Computing (GRAPHX). The earlier MapReduce had a great advantage.

(2) Active support from the development community. Spark is now on GitHub, and its rapid growth has been fueled by growing developers. There are at least nearly thousands of developers contributing code from more than 50 organizations, making the spark community the most active big data-processing development community today.

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Learn spark technology, adapt to big data development trend