sql grouping functions

8/6/2019 SQL Grouping Functions

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2010 IBM Corporation

V6R1: SQL Grouping FunctionsMultidimensional Results at the click of a Query

DB2 for IBM i

Tom McKinley ([email protected])IBM Systems and Technology GroupLab Services


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Whats in a name?

Industry refers to Grouping Sets and Super Groups (Rollup and Cube)collectively as Grouping Sets

Grouping Sets and Super Groups are sometimes referred to as Analytical SQL Grouping Functions

For clarity, this presentation will use the term Grouping Functions when

collectively describing Grouping Sets, Rollups, and Cubes


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Qtr1 Qtr4Qtr2 Qtr3

Selection can be performed usingany method available, includingparallel enabled methods

Hash Table Grouping

Qtr, Units

42007110Flange

12005680Widget

4200630Widget

420053Dome3200514Flange

320071Widget

4200683Widget

2200619Cog

420067Widget

Qtr Year UnitsPart

Collect all common input values into acommon bucket (by hash value)

The same input value willalways result in the samehash value

Only relevantinformation is stored

and the data is in noparticular order

Input: Join or Group By value

Output: Hash value

Aggregate onunits for eachgroup of quarters



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Radix Index Grouping

12005Widget

32007Widget

32005Flange

42005Dome

42007Flange

22006Cog

42006Widget

42006Widget

42006Widget

Qtr Year Part

RRNs

42007110Flange

12005680Widget4200630Widget

420053Dome

3200514Flange

320071Widget

4200683Widget

2200619Cog

420067Widget

Qtr Year UnitsPart

Given an index on Part, Year, Qtr,Apply local selection, and gather RRNs for each group of Quarters

Use RRNs to access the tablerows to gather the unitsinformation

Aggregate on units for eachgroup of quarters



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Grouping Functions Roadmap

Grouping Sets and Super Groups Defined

Grouping Functions Syntax and Examples

Grouping Functions Performance Considerations and Examples


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Grouping Sets and Super Groups Defined


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Grouping Sets and Super Groups (ROLLUP and CUBE)

Many BI applications involve hierarchical, multi-dimensional aggregate view of the data.

Current group by support permits grouping/aggregation data along one dimension SELECT COUNTRY, REGION, STORE, PRODUCT, SUM(SALES),

COUNT(*) FROM TRANS GROUP BY COUNTRY, REGION, STORE, PRODUCT

Users naturally view this data in multiple ways e.g. Roll result up to aggregate on the country and region (group by country, region) and then

to the overall total (no group by clause, whole table aggregation).

User may also want a different perspective e.g. group by region, product.

Currently, all these different viewings require different succinct queries.


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Grouping Sets and Super Groups

Grouping Sets and Super Groups allow a user to groupand aggregate data in multiple ways in one query.

4 new keywords enable new Grouping Functions support GROUPING SETS ROLLUP CUBE GROUPING Aggregate Function

Syntax dictates whether multiple sets in a query act in an additive or multiplicative fashion


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Grouping Functions Syntax and Examples


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Grouping Sets Example

SELECT * FROM ( SELECT COUNTRY, REGION, NULL , SUM(SALES)

FROM TRANS GROUP BY COUNTRY, REGION, NULLUNION ALL

SELECT COUNTRY, NULL , STORE, SUM(SALES)FROM TRANS GROUP BY COUNTRY, NULL, STORE )

Total sales grouped by (country, region) and by (country, store)

SELECT COUNTRY, REGION, STORE, SUM(SALES)FROM TRANS

GROUP BY GROUPING SETS ( (COUNTRY, REGION) ,

(COUNTRY, STORE) )

Logical Equivalent SQL UNION syntax:


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Grouping Sets Example

1,310,000-SWU.S.A.

100,000Bobs-Canada

350,000Barbs-U.S.A.

770,000Caining-U.S.A.

400,000Menes-U.S.A.

500,000Mills-U.S.A.

300,000Pensk-U.S.A.

200,000Shell-U.S.A.

140,000Targe-U.S.A.

440,000Toms-U.S.A.

150,000Wally-U.S.A.

550,000-SEU.S.A.

940,000-NWU.S.A.

450,000-NEU.S.A.

100,000-NWCanada

Sum(Sales)StoreRegionCountrySELECT

COUNTRY,REGION,

NULL ,SUM(SALES)FROM TRANS

GROUP BYCOUNTRY,

REGION,

NULL

SELECTCOUNTRY,

NULL ,STORE,

SUM(SALES)FROM TRANS

GROUP BYCOUNTRY,

NULL, STORE

SELECT COUNTRY, REGION, STORE, SUM(SALES)FROM TRANS GROUP BY GROUPING SETS((COUNTRY, REGION), (COUNTRY, STORE))

Store is NULLeven if Store is

Not Null Capable!


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Rollup Example

SELECT * FROM (SELECT COUNTRY, REGION, SUM(SALES)

FROM TRANS GROUP BY COUNTRY, REGION

UNION ALLSELECT COUNTRY, NULL, SUM(SALES)

FROM TRANS GROUP BY COUNTRY, NULL UNION ALL

SELECT NULL, NULL, SUM(SALES)FROM TRANS)

SELECT COUNTRY, REGION, SUM(SALES)FROM TRANS

GROUP BY ROLLUP (COUNTRY, REGION)

Logical equivalent SQL UNION syntax:

The ROLLUP operation generates a result set showingaggregates for a hierarchy of values in the selected columns


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Rollup Example

SELECT NULL,NULL,


SELECT COUNTRY,NULL, SUM(SALES)

FROM TRANS GROUPBY COUNTRY, NULL

SELECT COUNTRY,REGION,


GROUP BYCOUNTRY, REGION

1,310,000SWU.S.A.

550,000SEU.S.A.

940,000NWU.S.A.

450,000NEU.S.A.

100,000NWCanada

3,250,000-U.S.A.

100,000-Canada

3,350,000--

Sum(Sales)RegionCountry

Question: Is this data ordered?

SELECT COUNTRY, REGION, SUM(SALES) FROM TRANSGROUP BY ROLLUP (COUNTRY, REGION)


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Ordered Rollup Example

SELECT COUNTRY, REGION, SUM(SALES)FROM TRANS GROUP BY ROLLUP (COUNTRY, REGION)

ORDER BY 1 ASC,2 ASC

The ROLLUP operation generates a result set showing

aggregates for a hierarchy of values in the selected columns


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3,250,000-U.S.A.

1,310,000SWU.S.A.

550,000SEU.S.A.

940,000NWU.S.A.

450,000NEU.S.A.

100,000-Canada

100,000NWCanada

3,350,000--


SELECT COUNTRY, REGION, SUM(SALES)FROM TRANS GROUP BY ROLLUP (COUNTRY, REGION)ORDER BY 1 ASC, 2 ASC


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1,310,000SWU.S.A.

550,000SEU.S.A.

940,000NWU.S.A.

450,000NEU.S.A.

3,250,000-U.S.A.

100,000NWCanada

100,000-Canada

3,350,000--


SELECT COUNTRY, REGION, SUM(SALES)FROM TRANS GROUP BY ROLLUP (COUNTRY, REGION)ORDER BY 1 ASC,2 ASC


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Cube Example

SELECT COUNTRY, REGION, SUM(SALES) FROM TRANS

GROUP BY GROUPING SETS ((COUNTRY, REGION),(COUNTRY),

(REGION),())

SELECT COUNTRY, REGION, SUM(SALES) from TRANS GROUP BY CUBE (COUNTRY, REGION)

Is equivalent to the following Grouping Sets syntax:

The CUBE operation is a shorthand way to specify groupingover every possible dimension out of a given set of grouping

columns


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Cube Example

SELECT * FROM (SELECT COUNTRY, REGION, SUM(SALES) FROM TRANS

GROUP BY COUNTRY, REGION UNION ALL

SELECT COUNTRY, NULL, SUM(SALES) FROM TRANS GROUP BY COUNTRY, NULL

UNION ALLSELECT NULL, REGION, SUM(SALES) FROM TRANS

GROUP BY NULL, REGION UNION ALL

SELECT NULL, NULL, SUM(SALES) FROM TRANS)

SELECT COUNTRY, REGION, SUM(SALES) from TRANS GROUP BY CUBE (COUNTRY, REGION)

Logical equivalent SQL UNION syntax:


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Cube Example

SELECT NULL,REGION,

SUM(SALES) FROMTRANS

GROUP BY NULL,REGION

SELECT COUNTRY,NULL, SUM(SALES)

FROM TRANSGROUP BY

COUNTRY, NULL

SELECT COUNTRY,REGION,

SUM(SALES) FROMTRANSGROUP BY

COUNTRY, REGION

SELECT NULL,

NULL, SUM(SALES)FROM TRANS

3350000--

100000-Canada

3250000-U.S.A.

100000 NWCanada

450000 NEU.S.A.

940000 NWU.S.A.

550000SEU.S.A.

1310000SWU.S.A.

1310000SW-

550000SE-

1040000 NW-

450000NE-


SELECT COUNTRY, REGION, SUM(SALES) from TRANSGROUP BY CUBE (COUNTRY, REGION)


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GROUPING Aggregate functionGROUPING Aggregate function helps to differentiate between a groupingfunction over columns containing NULL values and a group where acolumn is set to NULL because it is not represented.Aggregate function produces a 0 if column is part of the grouping functionAggregate function produces a 1 if column is set to NULL because it is notrepresented

Example :SELECT A, B, GROUPING(B), SUM(D) FROM T1 GROUP BY ROLLUP (A, B)

GROUPING(B) returns a value of 0 for group 1: (A,B)GROUPING(B) returns a value of 1 for groups 2 and 3: (A,-),(-.-)

Helps to differentiate between group 1 result set where B is NULL andresult sets of groups 2 & 3

ROLLUP(AB) =(A,B), (A,-), (-,-)


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Multiplicative vs. Additive

CUBE and ROLLUP can appear as part of a GROUP BY or GROUPING

SETS list

When CUBE and ROLLUP expressions are combined in one set, they operatelike multipliers, forming additional set entries according to the definition of CUBE, ROLLUP

When the CUBE or ROLLUP are separate sets, they operate in an additivefashion

The use of parenthesis and the GROUPING SETS vs. GROUP BY clause willdictate how CUBE and ROLLUP expressions interact with each other


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Multiplicative vs. Additive Examples

EXAMPLE 3:

GROUP BY A, B, ROLLUP(C,D)Or GROUP BY GROUPING SETS ( ( A, B, ROLLUP(C,D) ) )

Parenthesis in BLUE specifies that those elements are multiplicative in nature if aROLLUP or CUBE exists.

GROUPING SETS clause with double parenthesis is multiplicative GROUP BY clause with ROLLUP or CUBE is multiplicative ROLLUP(C,D) expands to GROUPING SETS ((C,D), (C), ()) GROUP BY occurs in a multiplicative fashion to form:

GROUP BY GROUPING SETS ((a, b, c, d), (a, b, c), (a, b))


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Multiplicative vs. Additive Examples

EXAMPLE 4:

GROUP BY CUBE(A, B), ROLLUP(C, D), E OR GROUP BY GROUPING SETS ( ( CUBE(A,B), ROLLUP(C,D), E ) )

Parenthesis in BLUE specifies that those elements are multiplicative in nature if aROLLUP or CUBE exists

CUBE(A,B) expands to GROUPING SETS ((A,B), (A), (B), ())

ROLLUP(C,D) expands to GROUPING SETS ((C,D), (C), ())

GROUP BY occurs in a multiplicative fashion to form:

GROUPING SETS ((A, B C, D, E), (A, B, C, E), (A, B, E), (A, C, D, E), (A, C,E), (A, E), (B, C, D, E), (B, C, E), (B, E), (C, D, E), (C, E), (E))

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Grouping Functions Performance Tuning

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Performance Tuning Opportunities

Sound Indexing & Statistics Strategy

(ibm.com/servers/enable/site/education/ibo/record.html?indxng) Create Radix Indexes for common Grouping Set and ROLLUP sets Run Visual Explain to view query rewrites Use Index Advised to find holes in indexing strategy and temporary index creates

Sorted Aggregate Hash Table Creates Could be replaced by a permanent index if index encapsulates predicate selection, grouping

and aggregation columns. Index Advised can help with this Parallelism can greatly improve populate time of the hash table

Temporary Index Creates Could be replaced by a permanent index if index encapsulates predicate selection, grouping

and aggregation columns. Index Advised can help with this Can imply that the environment is memory constrained

Memory Constaints Grouping function queries are generally more memory intensive as they often union multiple

trees that create and interrogate temporary objects

Use feedback tools to determine the Optimizers fair share of memory

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Strategic Indexed Advised MechanismsVisual Explain

System wide index advice (V5R4) Data is placed into a DB2 table (QSYS2/SYSIXADV) Autonomic with no overhead

SQE Plan Cache (V5R4) No direct index advice

Index advice via Snapshot data or Visual Explain

SQE Plan Cache Snapshot (V5R4) Enhanced SQE index advised 3020 rows to show multiple indexes for same table Temporary index created

Detailed Database Monitor (V5R4) Enhanced SQE index advised 3020 rows to show multiple indexes for same table Temporary index created

IndexesAdvised

SQE PlanCache

QueryOptimization

SQL request

DetailedDB Monitor

Data

DebugJob Log

MessagesPrint SQLInformationMessages

VisualExplain

SummarizedDB Monitor

Data

SQE PlanCache

Snapshots

IndexesAdvised

SQE PlanCache

QueryOptimization

SQL request

DetailedDB Monitor

Data

DebugJob Log

MessagesPrint SQLInformationMessages

VisualExplain

SummarizedDB Monitor

Data

SQE PlanCache

Snapshots

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Grouping Set Index Advised ExampleSELECT REGION, COUNTRY, COUNT(TERRITORY) FROM CUST_DIM WHERE CONTINENT = 'AMERICA'

GROUP BY GROUPING SETS ((REGION),(COUNTRY))

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Grouping Set Index Advised Example

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Grouping Set Index Advised ExampleSELECT REGION, COUNTRY, COUNT(TERRITORY) FROM CUST_DIM GROUP BY GROUPING SETS ((REGION),(COUNTRY))

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Feedback Mechanism Changes for Grouping Sets

CHANGED

Visual Explain New icons: Multiple Aggregations, Temporary Distinct Hash TableDetailed Database Monitor Data SQL trace Grouping rows (3028 rows) will get cut for each ROLLUP and Grouping Set leg See V6R1 info Center doc for 3028 record changes

Indexes Advised System wide Index Advised strategy unchanged Indexes will be advised during normal optimization path

UNCHANGEDSQE Plan CacheSQE Plan Cache SnapshotsSummarized Database Monitor DataDebug Job Log MessagesPRTSQLINF Messages

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DB2 Family & MQTs Stage 2 V5R4

MQT Example:

CREATE TABLE Example_MQT AS(SELECT Geography, Region, Year, Month,SUM(Revenue) AS Total_Revenue, SUM(Quantity) AS Total_Quantity,COUNT(*) AS Rows_per_Group

FROM Example_TableGROUP BY Geography,Region,Year,Month)

DATA INITIALLY IMMEDIATEREFRESH DEFERRED

ENABLE QUERY OPTIMIZATIONMAINTAINED BY USER

Optimizer could use the MQT instead of fully executing the following query: SELECT Geography, Year,

SUM(Revenue) AS Total_Revenue, SUM(Quantity) AS Total_Quantity,FROM Example_Table WHERE Year IN (2004, 2005)

GROUP BY Geography, Year; white paper: ibm.com/servers/enable/site/education/abstracts/438a_abs.html

User responsible for keeping MQT data current and activating optimizer MQT awareness withQAQQINI options

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MQTs and Grouping SetsMQT matching strategy will look for an exact match of the grouping sets in thequery to grouping sets in an MQT.

Example :SELECT A, B, C, SUM(D) FROM T1 GROUP BY GROUPING SETS ((A), (B, C))

MQT1 :CREATE TABLE MQT1 AS SELECT A, SUM(D) as SUM_MQT1 FROM T1GROUP BY A

MQT2 :CREATE TABLE MQT2 AS SELECT B, C, SUM(D) as SUM_MQT2 FROM T1GROUP BY B, C

The MQTs can be used as follows:SELECT A, NULL, NULL, SUM_MQT1 FROM MQT1

UNION ALLSELECT NULL, B, C, SUM_MQT2 FROM MQT2

MQTs which provide a subset of the grouping sets asked for in the query can beunioned with a query that implements the remaining grouping sets

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MQTs and ROLLUPIf the query contains a ROLLUP, an MQT that does simple grouping or ROLLUPover the ROLLUP columns is useful

Example:SELECT A, B, C, SUM(D) FROM T1 GROUP BY ROLLUP (A, B, C)

MQT :SELECT A, B, C, SUM(D) as SUM_MQT FROM T1 GROUP BY A, B, C

The MQT can be used as follows:SELECT A, B, C, SUM(SUM_MQT) FROM MQT GROUP BY ROLLUP(A, B, C)

SUM(D) becomes a SUM(SUM) when the MQT is substituted. Other aggregateexpressions can be done with similar compensations. COUNT aggregate expression becomes SUM of the MQT COUNT MAX/MIN becomes MAX/MIN of the MQT MAX/MIN.

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MQTs with GROUPING aggregate functionExample :

SELECT A, B, C, SUM(D) FROM T1 GROUP BY ROLLUP (A, B, C)

MQT :SELECT A, B, C, E, GROUPING(E) as GE, SUM(D) as SUM_MQT FROM T1 GROUP BY ROLLUP(A, B, C, E)

The MQT can be used as follows:SELECT A, B, C, SUM_MQT FROM MQT WHERE GE = 1

Rows where GROUPING(E) = 1 are results for ROLLUP(A, B, C) Optimizer must be able to differentiate between result set for GS(A,B,C,E)

where E contains NULLs and GS(A,B,C,-), GS(A,B,-,-), GS(A,-,-,-) andGS(-,-,-,-)

MQT would not be usable without GROUPING(E) in the MQT definition

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MQTs and Grouping SetsMQTs with GROUPING SET, ROLLUP and CUBE syntax can be used to handlegrouping queries

Example :SELECT SUM(D) FROM T1 GROUP BY GROUPING SETS((A), (B), (C))SELECT SUM(D) FROM T1 GROUP BY GROUPING SETS((A), (B))SELECT SUM(D) FROM T1 GROUP BY GROUPING SETS((A), (C))SELECT SUM(D) FROM T1 GROUP BY GROUPING SETS((B), (C))SELECT SUM(D) FROM T1 GROUP BY (A)SELECT SUM(D) FROM T1 GROUP BY (B)SELECT SUM(D) FROM T1 GROUP BY (C)

Can be satisfied with MQT :SELECT A, B, C, SUM(D), GROUPING(A), GROUPING(B), GROUPING(C) asSUM_MQT FROM T1 GROUP BY GROUPING SETS((A), (B), (C))

MQTs specifying CUBE and ROLLUP tend to carry large volumes of data. Used whendisk space is plentiful and:

Contain commonly used grouping permutations Very commonly run CUBE and ROLLUP queries

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Summary

New Grouping Functions Allow for multiple Grouping operations in 1 query,usually using 1 pass through the data

GROUP BY GROUPING SETS((C1,C2,C3), (C1,C2,C3,C4),(C1,C2) GROUP BY ROLLUP (C1,C2,C3) GROUP BY CUBE(C1,C2)

Be careful not to Ask for more than you need.

Use Visual explain to understand and tune query before you run it. Index advise is Key

Consider MQTs Solve these kinds of queries Provide great performance for expanded use of this grouping technology

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V6R1 IndexEnhancements

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V6R1 Creation of Index with Derived values

Creation of indexes with derived values via SQL

CREATE INDEX STAR100G.ODERPRIORITYUPPER ONSTAR100G.ITEM_FACT ( UPPER(ORDERPRIORITY ) AS UORDERPRIORITYASC);

CREATE ENCODED VECTOR INDEX STAR100G.YEARQTR ONSTAR100G.ITEM_FACT (YEAR(ORDERDATE) AS ORDYEAR ASC,

QUARTER(ORDERDATE) AS ORDQTR ASC);CREATE INDEX STAR100G.TOTALEXTENDEDPRICE ON

STAR100G.ITEM_FACT ( QUANTITY * EXTENDEDPRICE AS TOTEXTPRICEASC);

* BEWARE, THERE ARE SOME RESTRICTIONS ON WHAT QUERY OPTIMIZER CANUSE

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V6R1 Enhanced Native access to the SQL Index

Specify format name And table columns to be added to that format.

CREATE INDEX STAR100G.SHIPMODE ON STAR100G.ITEM_FACT

(SHIPMODE ASC, ZIPCODE ASC ) RCDFMT SHPMODEZIP ADDCUSTNAME, SHIPADDR;

CREATE INDEX STAR100G.SHIPMDMON ON STAR100G.ITEM_FACT(SHIPMODE ASC, MONTH(SHIPDATE AS SHIPMON for COLUMNSHIPMON ASC) RCDFMT SHPMODEMON ADD CUSTNAME, SHIPADDR,COMMITDATE;

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C i d f SQL


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Create sparse indexes from SQL

Support of WHERE clause on SQL create index

CREATE INDEX STAR100G.FASTDELIVER ON STAR100G.ITEM_FACT (SHIPMODEASC) WHERE SHIPMODE = 'NEXTDAYAIR' OR SHIPMODE = 'COURIER ';

CREATE INDEX STAR100G.FASTDELIVR ON STAR100G.ITEM_FACT (SHIPMODE ASSHIPMODE FOR COLUMN SHIPMODE ASC) WHERE SHIPMODE = 'NEXTDAYAIR'OR SHIPMODE = 'COURIER' RCDFMT FASTDLVR ADD ORDERKEY, SHIPDATE,COMMITDATE, RECEIPTDATE, SHIPPRIORITY;

Limitations NOT USED BY THE QUERY OPTIMIZER (BOTH SQE AND CQE)

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Wh h ld I D i d IX t?


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When should I use Derived IX support?

Could replace some logical files with SQL indexes for use by Nativeprograms. Modernize those objects Big logical pagesize

Derived indexes may be useful for Case insensitive searches Data extracted from a column (i.e. SUBSTR, YEAR, MONTH..

Results of operations ( COL1+COL2 , QTY * COST) Might be useful to allow Index only access in more cases Reduce table scans Index Used more often for local selection

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Wh Sh ld I WHERE Cl t


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When Should I use WHERE Clause support

In general its not a good idea to build indexes with the WHERE clause Not yet useable by the Optimizer May be too specific, Only useable by small number of statements DO NOT Replace general purpose index with multiple Sparse indexes

CREATE INDEX ORDERYEAR on ORDERS (YEAR ASC) NOT the following

CREATE INDEX ODERYEAR1 on ORDERS(YEAR ASC)WHERE YEAR=2006



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Are you experiencing performance problems?


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IBM DB2 for i Center of Excellence

Database modernizationDB2 Web QueryDatabase architecture and design

DB2 SQL performance analysis and tuningData warehousing and Business IntelligenceDB2 for i education and training

Contact: Mike Cain [email protected] Systems and Technology Group

Rochester, MN USA

Are you experiencing performance problems?

Are you using SQL?

Are you getting the most out of DB2 for i?

Need help?
mailto:[email protected]:[email protected]


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Thank You

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