- MySQL 8 for Big Data
- Shabbir Challawala Jaydip Lakhatariya Chintan Mehta Kandarp Patel
- 84字
- 2021-08-20 10:06:08
Organizing data in Hadoop
The next step is to organize data in the Hadoop filesystem once the data has been acquired and loaded to MySQL. Big Data requires some processing to produce analysis results where Hadoop is used to perform highly parallel processing. Hadoop is also a highly scalable distributed framework and is powerful in terms of computation. Here, the data is consolidated from different sources to process the analysis. To transfer the data between MySQL tables to HDFS, Apache Sqoop will be leveraged.
推薦閱讀
- Microsoft Application Virtualization Cookbook
- OpenCV 3和Qt5計(jì)算機(jī)視覺應(yīng)用開發(fā)
- Web Application Development with MEAN
- 零基礎(chǔ)學(xué)單片機(jī)C語言程序設(shè)計(jì)
- 批調(diào)度與網(wǎng)絡(luò)問題的組合算法
- 深入剖析Java虛擬機(jī):源碼剖析與實(shí)例詳解(基礎(chǔ)卷)
- 石墨烯改性塑料
- 實(shí)戰(zhàn)Python網(wǎng)絡(luò)爬蟲
- Python面試通關(guān)寶典
- C++17 By Example
- Java EE項(xiàng)目應(yīng)用開發(fā)
- Java EE 7 Development with WildFly
- The Applied Data Science Workshop
- Cinder:Begin Creative Coding
- PHP從入門到精通(第7版)