By Aaron Cordova, Billie Rinaldi, Michael Wall
Wake up to hurry on Apache Accumulo, the versatile, high-performance key/value shop created through the nationwide safety corporation (NSA) and in line with Google’s BigTable information garage approach. Written by way of former NSA group contributors, this accomplished educational and reference covers Accumulo structure, program improvement, desk layout, and cell-level security.
With transparent info on method management, functionality tuning, and most sensible practices, this booklet is perfect for builders looking to write Accumulo functions, directors charged with fitting and preserving Accumulo, and different pros drawn to what Accumulo has to supply. you'll find every thing you can use the program fully.
Get a high-level advent to Accumulo’s structure and information model
Take a swift travel via unmarried- and multiple-node installations, info ingest, and query
easy methods to write Accumulo functions for a number of use circumstances, according to examples
Dive into Accumulo internals, together with details now not to be had within the documentation
Get designated details for fitting, administering, tuning, and measuring performance
examine most sensible practices in keeping with profitable implementations within the field
locate solutions to universal questions that each new Accumulo consumer asks
Read Online or Download Accumulo: Application Development, Table Design, and Best Practices PDF
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Extra info for Accumulo: Application Development, Table Design, and Best Practices
The Bigtable paper describes two types of compression. One compresses long com‐ mon strings across a large window, and the other does compression over small win‐ dows of data. These types of custom compression are not implemented in Accumulo. Robust Timestamps When Accumulo tablet servers are assigning timestamps to key-value pairs, Accu‐ mulo ensures that the timestamps are internally consistent. Accumulo only assigns new timestamps that are later than the most recent timestamp for a given tablet.
Having a separate storage layer allows Accumulo to balance the responsibility for serving portions of tables independently of where they are stored, although data tends to be served from the same server on which it is stored. Like Accumulo, HDFS is a distributed application, but one that allows users to view a collection of machines as a single, scalable filesystem. HDFS files can be very large, up to terabytes per file. HDFS automatically breaks these files into blocks—by default 64 MB or 128 MB in size depending on the version of HDFS—and distributes these blocks across the cluster uniformly.
Table 1-2. Accumulo and HBase Bigtable naming conventions Apache Accumulo Bigtable Apache HBase Tablet Tablet Region Tablet Server Tablet Server Region Server Minor Compaction Minor Compaction Flush 34 | Chapter 1: Architecture and Data Model Major Compaction Merging Compaction Minor Compaction (Full) Major Compaction Major Compaction Major Compaction Write-Ahead Log Commit Log Write-Ahead Log HDFS GFS HDFS Hadoop MapReduce MapReduce Hadoop MapReduce MemTable MemTable MemStore RFile SSTable HFile ZooKeeper Chubby ZooKeeper ZooKeeper ZooKeeper is a highly available, highly consistent, distributed application in which all data is replicated on all machines in a cluster so that if one machine fails, clients read‐ ing from ZooKeeper can quickly switch over to one of the remaining machines.