Apache HBase Primer by Deepak Vohra

By Deepak Vohra

Research the basic foundations and ideas of the Apache HBase (NoSQL) open resource database. It covers the HBase info version, structure, schema layout, API, and management. Apache HBase is the database for the Apache Hadoop framework. HBase is a column relatives dependent NoSQL database that offers a versatile schema version.

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Compaction Compaction is the process of creating a larger file by merging smaller files. Compaction can become necessary if HBase has scanned too many files to find a result but is not able to find a result. hstore. max, parameter compaction is performed to merge files to create a larger file. Instead of searching multiple files, only one file has to be searched. Two types of compaction are performed: minor compaction and major compaction. Minor compaction just merges two or more smaller files into one.

Leaf index blocks and bloom filter blocks also are cached. Smaller block sizes are used for faster random access. Smaller block sizes provide smaller read and faster in-block search. But smaller blocks lead to a larger block index and more memory consumption. For faster scans, use larger block sizes. The number of key-value pairs that fit an average block may also be determined. The block format is shown in Figure 2-27. Figure 2-27. Block format Compression and data block encoding (PREFIX, DIFF, FAST_DIFF, PREFIX_TREE) minimizes file sizes and on-disk block sizes.

The client gets the path for the block and opens the file with FileInputStream. shortcircuit. size = 1MB vs. 28GB of non-heap memory usage. Checksums HDFS checksums are not inlined. They are two files per block, one for data and one for checksums, as shown in Figure 2-29. 40 CHAPTER 2 ■ APACHE HBASE AND HDFS Figure 2-29. Two files per block Random positioned read causes two seeks. 94. HFile v 2-1 writes checksums per HFile block. The HFile data block chunk and the Checksum chunk are shown in Figure 2-30.

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