How does indexing improve query performance?
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Answer Posted / sri krishna
Teradata automatically Creates the Primary index , if not
specified by the DDl for Table .Some of the Other Types of
indexes are
Secondary Index
Partitioned Primary Index
Join Index
Primary Index :- the PI is the way , Teradata Distributes
the Data , Accesses the Data to/from Amps. By Using the
Primary Index with Value or Range of Values in the Where
Clause of the Query , the operation Becomes a Single AMP/
Few amp aperation instead of all amp operation . the Access
path is
Rowhash of the Pi is known --> Amp of the Column along
with rowid of the Column . (1 Amp Ops)
Results
1. Highly Optimised Query Retrival
2. less Cost per Retrival
Secondary Index / Join Indexes :-
Creates a Secondary Index / Joinindex / Hashindex
Subtable , which maps the Column/s of the SI and the PI
Hash /Join(Frequently used Columns in two tables in this
Case ) , The operations , if using these Indexes are
basically 2 or more amp operation .
Results
1. Quicker Query Retrival time than a full table scan .
2. costs less on the Resources than a FTS
3. the Performance is improved if the JI is used by the
Optimizer
cons --
1. Additional Space Req. for the Subtables
2. need to be droped and recreated for Loads to happen
(Multi Load , FastLoad)ect , which is a real PAIN !!!
3.still be a 2 amp operation when compared to PI Retrival
for a SI.
PPI :-
Partitioned Primary Indexes are Created so as to divide the
table onto partitions based on Range or Values as Required .
the data is first Hashed into Amps , then Stored in amps
based on the Partitions !!! which when Retrived for a
single partition / multiple Partitions , will be a all amps
Scan, but not a Full Table Scan !!!! . this is effective
for Larger Tables partitioned on the Date Specially !!!
there is no extra Overhead on the System (no Spl Tables
Created ect )
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