BigTable

From Wikipedia, the free encyclopedia

This article may require cleanup to meet Wikipedia's quality standards.
Please discuss this issue on the talk page or replace this tag with a more specific message.
This article has been tagged since January 2007.

BigTable is a compressed, high performance and proprietary database built on Google File System (GFS), Chubby Lock Service and a few other Google programs; it is currently not distributed or used outside of Google. It began in 2004 ^[1] and is now used by a number of Google applications, such as MapReduce, which is often used for generating and modifying data stored in BigTable^[2] Google Reader ^[3], Google Maps^[4], Google Print, "My Search History", Google Earth, Blogger.com, Google Code hosting, and Orkut^[4]. Google's reasons for developing its own database include licensing costs, scalability, and better control of performance characteristics.^[5]

It is a fast and extremely large-scale system database, with a focus on quick reads from columns, not rows. It's designed to scale into the petabyte range across hundreds or thousands of machines, and to make it easy to add more machines to the system and automatically start taking advantage of those resources without any reconfiguration" ^[6]. Each table has multiple dimensions (one of which is a field for time, allowing versioning). Tables are optimized for GFS by being split into multiple tablets- segments of the table as split along a row chosen such that the tablet will be ~200 megabytes in size. When sizes threaten to grow beyond a specified limit, the tablets are compressed using the algorithms BMDiff and Zippy, which are described as not as space-optimal as LZW but more efficient in terms of computing time. The locations in the GFS of tablets are recorded as database entries in multiple special tablets, which are called "META1" tablets. META1 tablets are found by querying the single "META0" tablet, which typically has a machine to itself since it is often queried by clients as to the location of the "META1" tablet which itself has the answer to the question of where the actual data is located. Like GFS' master server, the META0 is not generally a bottleneck since the processor time and bandwidth necessary to discover and transmit META1 locations is minimal and clients aggressively cache locations to minimize queries.

[edit] See also

[edit] References

^ "First an overview. BigTable has been in development since early 2004 and has been in active use for about eight months (about February 2005)." Google's BigTable
^ "Bigtable can be used with MapReduce, a framework for running large-scale parallel computations developed at Google. We have written a set of wrappers that allow a Bigtable to be used both as an input source and as an output target for MapReduce job". pg 3 of "Bigtable: A Distributed Storage System for Structured Data", 2006
^ "Reader is using Google's BigTable in order to create a haven for what is likely to be a massive trove of items." Official Google Reader blog.
^ ^a ^b "There are currently around 100 cells for services such as Print, Search History, Maps, and Orkut." Google's BigTable
^ "We have described Bigtable, a distributed system for storing structured data at Google....Our users like the performance and high availability provided by the Bigtable implementation, and that they can scale the capacity of their clusters by simply adding more machines to the system as their resource demands change over time...Finally, we have found that there are significant advantages to building our own storage solution at Google. We have gotten a substantial amount of flexibility from designing our own data model for Bigtable." from the Conclusion of "Bigtable: A Distributed Storage System for Structured Data", 2006
^ *"Database War Stories #7: Google File System and BigTable"