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Very large Database
Kazem Taghandiky University of [email protected]:09335816144
In The Name Of God
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A very large database, or VLDB, is a database that contains an extremely high number of tuples (database rows), or occupies an extremely large physical file system storage space. The most common definition of VLDB is a database that occupies more than 1 terabyte or contains several billion rows, although naturally this definition changes over time
If I updated this list in 3-5 years, all of the fixed measurements would probably increase by a factor of 10X to 100X, maybe more. Probably the most relevant description of a “Large Database” is one that is causing you pain and forcing you to consider other optionsThe definition of large database is always changing,
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1. Introduction
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VLDB is a premier annual international forum for data management and database researchers, vendors, practitioners, application developers, and users. The conference will feature research talks, tutorials, demonstrations, and workshops. It will cover current issues in data management, database and information systems research. Data management and databases remain among the main technological cornerstones of emerging applications of the twenty-first century
Importance
1. Introduction
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The Factors that Define a Large Database
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1. Introduction
ThroughputData volume
Hardware
Software
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2. DBMS vs. VLDB
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2-1. Examples of VLDB
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Loading a big database for a takes a long time.
Adding rows to an existing database is slow. Adding or removing a column takes my table
offline for a long time. Adding an index takes my table offline long
time. Backup is difficult. (Not in this talk.)These activities are painless for small data, but can bepainful for big data.
3. Challenges
Some of the top challenges I hear:
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1.Partitioning addresses key issues in supporting very large tables and indexes by letting you decompose them into smaller components called partitions. SQL queries and DML statements do not need to be modified in order to access partitioned tables.
Each partition of a table or index must have the same logical attributes, such as column names,2.Data types, and3.constraints,but each partition can have separate physical attributes such as table spaces.
3-1. Techniques for challenge
Partitioning
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Range partitioning divides a table into partitions based on a range of values. You can use one or more columns to define the range specification for the partitions.
3-1. Techniques for challenge
Overview of Partitioning Methods
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3-1. Techniques for challenge
Overview of Partitioning Methods
List PartitioningYou do this by specifying a list of discrete values for the partitioning key in the description for each partition
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HASH partitioning With this type of partitioning, a partition is selected based on the value returned by a user-defined expression that operates on column values in rows to be inserted into the table
3-1. Techniques for challenge
Overview of Partitioning Methods
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Oracle : Tables can be partitioned into up to 64,000 separate partitions
SQL Server :
3-1. Techniques for challenge
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Table partitioning delivers advantages in three main areas
• performance
• maintenance
• availability.
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3-1. Techniques for challenge
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You can use the data compression feature to help compress the data inside a database, and to help reduce the size of the database. In addition to saving space, data compression can help improve performance of I/O intensive workloads because the data is stored in fewer pages and queries need to read fewer pages from disk. However, extra CPU resources are required on the database server to compress and decompress the data,
Data Compression
3-1. Techniques for challenge
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ImplementationRow Compression
•It reduces the metadata overhead that is associated with the record. This metadata is information about columns, their lengths and offsets. In some cases, the metadata overhead might be larger than the old storage format.•It uses variable-length storage format for numeric types (for example integer, decimal, and float) and the types that are based on numeric (for example date time and money).•It stores fixed character strings by using variable-length format by not storing the blank characters
3-1. Techniques for challenge
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ImplementationPage Compression
Compressing the leaf level of tables and indexes with page compression consists of three operations in the following order:1.Row compression2.Prefix compression3.Dictionary compression
3-1. Techniques for challenge
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3-1. Techniques for challenge
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4. Practical
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4. Practical
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4. Practical
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Thank You For Your Attention
