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Comparison to other indexes
Additional indexes
Optimizing performance for ad hoc joins
Table 4-7: HNG advantages/disadvantages
Advantages
Due to compression algorithms used,
disk space requirements can be
reduced without sacrificing
performance.
If the column has a high number of
unique values, this is the fastest index,
with few exceptions described below.
•
needs less disk space than
HNG
efficiently.
•
In choosing between
unique values. Use
HNG
1000.
The High_Group index is also appropriate for an
To gain the fastest processing of ad hoc joins, create a Low_Fast or
High_Group index on all columns that may be referenced in:
•
clauses of ad hoc join queries
WHERE
•
clause conditions of ad hoc join queries outside of aggregate
HAVING
functions
For example:
SELECT n_name, sum(l_extendedprice*(1-l_discount))
AS revenue
FROM customer, orders, lineitem, supplier,
nation, region
WHERE c_custkey
AND o_orderkey
CHAPTER 4
Adaptive Server IQ Indexes
Disadvantages
This index is not recommended for
queries.
BY
Index not possible if uniqueness enforced.
Cannot use this index if data in your
columns is
FLOAT
> 255 bytes.
VARCHAR
but can't perform
HG
and
, the determining factor is the number of
LF
HNG
when the number of unique values is greater than
HNG
= o_custkey
= l_orderkey
GROUP
,
,
,
, or
REAL
DOUBLE
BIT
GROUP BY
column.
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