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Crosswalk tables are often employed within or in parallel to enterprise systems, especially when multiple systems are interfaced or when the system includes legacy system data. In the context of Interfaces, they function as an internal extract, transform, load (ETL) mechanism. For example, this is a metadata crosswalk from MARC standards to ...
Partitioning aims to distribute data and query load evenly across nodes. With ideal distribution, system capacity scales linearly with added nodes—ten nodes should process ten times the data and throughput of a single node. Uneven distribution, termed skew, reduces partitioning efficiency. Partitions with excessive load are called hot spots. [1]
In SQL the UNION clause combines the results of two SQL queries into a single table of all matching rows. The two queries must result in the same number of columns and compatible data types in order to unite. Any duplicate records are automatically removed unless UNION ALL is used.
Horizontal partitioning splits one or more tables by row, usually within a single instance of a schema and a database server. It may offer an advantage by reducing index size (and thus search effort) provided that there is some obvious, robust, implicit way to identify in which partition a particular row will be found, without first needing to search the index, e.g., the classic example of the ...
In SQL:1999 a recursive (CTE) query may appear anywhere a query is allowed. It's possible, for example, to name the result using CREATE [ RECURSIVE ] VIEW . [ 16 ] Using a CTE inside an INSERT INTO , one can populate a table with data generated from a recursive query; random data generation is possible using this technique without using any ...
A join clause in the Structured Query Language combines columns from one or more tables into a new table. The operation corresponds to a join operation in relational algebra . Informally, a join stitches two tables and puts on the same row records with matching fields : INNER , LEFT OUTER , RIGHT OUTER , FULL OUTER and CROSS .
Normalization splits up data to avoid redundancy (duplication) by moving commonly repeating groups of data into new tables. Normalization therefore tends to increase the number of tables that need to be joined in order to perform a given query, but reduces the space required to hold the data and the number of places where it needs to be updated if the data changes.
SELECT is the most common operation in SQL, called "the query". SELECT retrieves data from one or more tables, or expressions. Standard SELECT statements have no persistent effects on the database. Some non-standard implementations of SELECT can have persistent effects, such as the SELECT INTO syntax provided in some databases. [4]