Bigtable is a distributed storage system developed at Google to manage large amounts of structured data across thousands of servers. It provides a flexible data model with rows and columns that can be queried and modified in real time. Bigtable was designed as Google needed a system that could scale enormously without compromising performance. It has been successfully used by many Google products and services that require fast access to very large datasets, such as web search, Google Maps, and Google Analytics.

1. Bigtable: A Distributed Storage System
Presenter: Ku. Devyani B.Vaidya

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Bigtable: A Distributed Storage System
1. Introduction
2. What is a Bigtable?
3. Why not A DBMS?
4. Data model: Row
Column
Timestamps
5. APIs
6. Building Blocks
8. Conclusion
7.Real Applications

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Introduction
• BigTable is a distributed storage system
for managing structured data.
• Designed to scale to a very large size
- Petabytes of data across thousands of
servers
• Used for many Google projects
- Web indexing, Personalized Search, Google
Earth, Google Analytics, Google Finance, …
• Flexible, high-performance solution for
all of Google’s products

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What is a Bigtable?
• “A BigTable is a sparse, distributed,
persistent multidimensional sorted map. The
map is indexed by a row key, a column key,
and a timestamp; each value in the map is an
uninterpreted array of bytes.”

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Why not A DBMS?
• Few DBMS’s support the requisite scale
– Required DB with wide scalability, wide
applicability, high performance and high
availability
• Couldn’t afford it if there was one
– Most DBMSs require very expensive
infrastructure
• DBMSs provide more than Google needs
– E.g., full transactions, SQL
• Google has highly optimized lower-level systems
that could be exploited
– GFS, Chubby, MapReduce, Job scheduling

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Data model: Row
• Row keys are arbitrary strings
• Row is the unit of transactional consistency
• Data is maintained in lexicographic order by row
key
• Rows with consecutive keys (Row Range) are
grouped together as “tablets”.

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Data model: Column
• Column keys are grouped into sets called “column
families”, which form the unit of access control.
• Column key is named using the following syntax:
family :qualifier
• Access control and disk/memory accounting are
performed at column family level

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Data model: timestamps
• Each cell in Bigtable can contain multiple versions
of data, each indexed by timestamp
• Timestamps are 64-bit integers
• Assigned by:
– Bigtable
– Client application
• Data is stored in decreasing timestamp order, so
that most recent data is easily accessed
– Application specifies how many versions (n) of data items
are maintained in a cell
- Bigtable garbage-collects cell versions automatically.

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Data Model
Example: Web Indexing

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Data Model

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Data Model
Row

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Data Model
Columns

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Data Model
Cells

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Data Model
timestamps

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Data Model
Column family

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Data Model
Column family
family: qualifier

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Data Model
Column family
family: qualifier

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APIs
•The Bigtable API provides functions :
- Creating and deleting tables and column families.
-Changing cluster , table and column family
metadata.
-Support for single row transactions
-Allows cells to be used as integer counters

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Building Blocks
. Bigtable uses the distributed Google File
System (GFS) to store log and data files
• The Google SSTable file format is used
internally to store Bigtable data
• An SSTable provides a persistent , ordered
immutable map from keys to values

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Real Applications
•Google Analytics
http://analytics.google.com
•Google Earth & Google Maps
http://earth.google.com
•Personalized Search
www.google.com/psearch
•Web Indexing
•Google Finance
•Orkut
•Writely

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Conclusion
• Bigtable has achieved its goals of high performance,
data availability and scalability.
It has been successfully deployed in real apps
(Personalized Search, Orkut, GoogleMaps, …)
• Significant advantages of building own storage
system like flexibility in designing data model, control
over implementation and other infrastructure on which
Bigtable relies on.

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Source
1. www.google.com
2. www.studymafia.org

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©2007 The Board of Regents of the University of Nebraska. All rights reserved.
Thanks