Chapter 1. Introducing HBase
Figure 1.1. Providing web-search results using Bigtable, simplified. The crawlers—applications collecting web pages—store their data in Bigtable. A MapReduce process scans the table to produce the search index. Search results are queried from Bigtable to display to the user.
Figure 1.2. The HBase Master status page. From this interface, you can get a general sense of the health of your installation. It also allows you to explore the distribution of data and perform basic administrative tasks, but most administration isn’t done through this interface. You’ll learn more about HBase operations in chapter 10.
Chapter 2. Getting started
Figure 2.1. HBase write path. Every write to HBase requires confirmation from both the WAL and the MemStore. The two steps ensure that every write to HBase happens as fast as possible while maintaining durability. The MemStore is flushed to a new HFile when it fills up.
Figure 2.2. HBase read path. Data is reconciled from the BlockCache, the Mem-Store, and the HFiles to give the client an up-to-date view of the row(s) it asked for.
Figure 2.3. Minor compaction. Records are read from the existing HFiles and combined into a single, merged HFile. That new HFile is then marked as the new canonical data on disk, and the old HFiles are deleted. When a compaction is run simultaneously over all HFiles in a column family, it’s called a major compaction.