sap hana_join types

8/18/2019 SAP HANA_Join Types

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©SAP AG HA300 2-2

© 2012 SAP AG. All rights reserved. 2

At the end of this Lesson you will be able to:

Objectives

Connecting Tables

Explain differences between Inner Join, Left Outer Join,

Right Outer Join, Full Outer Join, Text Join and

referential Join when connecting tables.

Explain how using Standard Union and Union with

constant values.



©SAP AG HA300 2-4


This module covers the following topics:

Overview

Connecting Tables

How to connect tables using

Inner Join

Left Outer Join

Right Outer Join

Full Outer Join

Text Join

Referential Join

Union



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Join Types – Definitions and Referential Integrity

Join Type Use when you need to

report on…

Be aware that…

INNER facts with matching dimensions

only

facts without any dimension will be excluded

dimensions without any fact will be excluded

JOIN is always performed

LEFT OUTER all posted facts whether there is

a matching dimension or not

dimensions without any fact will be excluded

best for performance because JOIN is omissible

RIGHT OUTER all dimensions whether there

are matching facts or not

facts without any dimension will be excluded

JOIN is always performed

REFERENTIAL facts for the requested

dimensions AND referential integrity is

ensured

it is the default join type

acts as an INNER for Attributes Views join on attribute views is “optional”, which facts are

returned will depend on which attributes are queried for

TEXT an SAP dimension table joined

to a text table for translation

purpose

only available for Attribute Views with SAP ERP tables

(SPRAS field) or equivalent design

acts as an INNER

Referential Joins

Is semantically a inner join that assume that referential integrity is given which means that theleft table always have an corresponding entry on the right table. It could be used in e.g. data

foundation for header-item relations where it can be assumed that for each item a header

exists. It can be seen as an optimized or faster inner join where the right table is not checked if

no field from the right table is requested. That means that the Referential Joins will be only

executed, when fields from both tables are requested. Therefore, if a field is selected from the

right table it will act similar to inner join, and if no fields from the right table is selected it will

act similar to a left outer join. From performance perspective, the Left Outer Join are almost

equally fast as Referential Join, while the Inner Join is usually slower due to the fact, that the

join is always executed.

Referential joins should be used with caution since it assumes that referential integrity is

ensured. The only valid scenario for the Referential Join is that (a) it is 100% guaranteed that

for each row in one table, there is at least one join partner in the other table, and (b) that holds

true in both directions (c) at all times. If that is not the case then referential joins have the

possibility to give incorrect calculations if the referential integrity is not met – meaning if a

delivery header is created but the items is not processed until a later stage then any

calculations that use referential joins will be incorrect.



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Attribute View

Inner Join – Attribute View

Connecting Tables

Customer (3 & 4) is not

returned due to nocorresponding entry (TX) in

the state table.

Inner Join returns rows when there is at least one match in both sides of the join.

Inner is used even if it’s not added.



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Inner Join – Analytical View

Connecting Tables

Analytical

View

Be aware that Inner Joinslose facts with fragmented

dimensions. Order (4 & 77)

lost due to no

corresponding customer

and state record



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Inner Join and Design Time Filters

Connecting Tables

Design time filter applied ( AGE < 13)

of left/central table

Design time filter applied to (STATE = MI)

on right table

Both design time filters are applied first

before the join is executed



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Attribute View

Left Outer Join – Attribute View

Connecting Tables

No matches for TX in the right table.

Left Outer Join returns all rows from the left

table even if there are no matches in the

right table.

This join is popular in Analytical Views

whereby the Attribute view is joined to the

fact table.



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Left Outer Join – Analytical View

Connecting Tables

Analytical

View

Customer (TOM) is

not returned due to no

corresponding sale

item record in sales

order table.



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Left Outer Join and Design Time Filters

Connecting Tables

Design time filter applied ( AGE < 13)

of left/central table

Design time filter applied to (STATE = MI)

on right table

Filters are applied to both tables and then

afterwards the join is executed.

Due to the left outer join TOM will be included in

the result set even though he resides in TX



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Right Outer Join – Attribute View

Connecting Tables

Alabama is included in the result set,

though there is no match in the left

table.

Attribute View Right Outer Join returns all the rows from

the right table, even if there are no

matches in the left table.

Right outer join is rarely used, be aware, that the number of records in the result set is

determined by the number of records in the right table. This means that if there is a 1:nrelationship the number of records can be greater that the number of records in the left table.



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Right Outer Join – Analytical View

Connecting Tables

Right Outer Join

results in NULL

measure.

Analytical

View



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Full Outer Join

Connecting Tables

STATE SNAME

? ? ? ? AL ALABAMA

1 WERNER 10 MI MI MICHIGAN

2 MARK 11 MI MI MICHIGAN

3 TOM 12 TX ? ?

4 BOB 13 TX ? ?

C_ID CNAME AGE STATE

Full Outer Join is neither left nor

right - it's both. It includes all therows from both of the tables or result

sets participating in the Join.

When no matching rows exist for

rows on the left side or right side of

the Join, you see NULL values.

Be aware that Full Outer Joins make up facts for unused dimension entries (ALABAMA)



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Text Join

Connecting Tables

Text Join are used to join a text

table to a master data table.

Text Joins acts as a Left Outer join

and can be used with SAP tables

where the language column

(SPRAS) is present.

For each attribute it is possible to

define a description mapping that

will be specific to the end users

language.



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Join Types – Text Join for multilingual reporting

Text Join is used whentranslation for a dimension is

available

Designed for ERP table (and

typically SPRAS field)

User language is used as a filter

at runtime to find the right

translation for that attribute



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Referential Join

Connecting Tables

Relies on Referential Integrity Each entry in the left table MUST havea corresponding entry in the right table

Optimized for performance Join is only performed if at least one

field from the right table is requested.

Like an Inner Join when join is

executed

When field from both tables are

requested an inner Join is performed.

Only available in OLAP engine Referential join is a feature availableonly in OLAP engine, when testing

Attribute Views outside the context of a

Analytical view then the Join Engine

will perform a Inner Join.

Is semantically a inner join that assume that referential integrity is given which means that the

left table always have an corresponding entry on the right table. It could be used in e.g. datafoundation for header-item relations where it can be assumed that for each item a header

exists.

It can be seen as an optimized or faster inner join where the right table is not checked if no

field from the right table is requested.

That means that the Referential Joins will be only executed, when fields from both tables are

requested. Therefore, if a field is selected from the right table it will act similar to inner join,

and if no fields from the right table is selected it will act similar to a left outer join.

From performance perspective, the Left Outer Join are almost equally fast as Referential Join,

while the Inner Join is usually slower due to the fact, that the join is always executed.



©SAP AG HA300 2-18


Referential Join – Attribute View

Connecting Tables

*** Referential join is a feature available only in OLAP engine, when testing

Attribute Views outside the context of a Analytical view then the Join Engine will

perform a Inner Join. As a result TOM and BOB will not be returned.



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Referential Join – Analytical View

Connecting Tables

*** TOM is not returned due to no

corresponding facts in the sales table

*** The Amount includes all facts including Customer 77 and BOBs

order even through master records do not exist reason is when

only non-key fields are selected from the left table, all joins to

other tables will be omitted

*** Customer 77, TOM and BOB are not returned since C_ID is a Joined key field

resulting in an Inner Join. BOB has no corresponding Texas description and TOM has no

corresponding facts.



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Referential Join – Using MDX

Connecting Tables

No referential integrity

of data in both tables

No Join processed

Like Inner Join

Referential joins should be used with caution since it assumes that referential integrity

is ensured.The only valid scenario for the Referential Join is that (a) it is 110% guaranteed that for each

row in one table, there is at least one join partner in the other table, and (b) that holds true in

both directions (c) at all times.

If that is not the case then referential joins have the possibility to give incorrect calculations if

the referential integrity is not met – meaning if a delivery header is created but the items is not

processed until a later stage then any calculations that use referential joins will be incorrect.

Referential Join cannot be used if a filter is set on a field in the right table.



©SAP AG HA300 2-21


Calculation View- Join vs. Union

Connecting Tables

Caution!! Do not JOIN Analytical Views, this could lead to performance

implications. Instead use Union with constant values when working withmultiple fact tables



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Unions

Connecting Tables

Unions are used to combine the result-set of two or more SELECT statements.

The Union operation is popular for combining plan and actual values in CO-PA.

Note that Unions are not supported in modeled artifacts (Attribute Views or Analytical

Views) and can only be realized in Calculation Views.

Refrain from Joining Analytical views; rather use Unions with Constant values.

Unions with Constant values are supported within Graphical Calculation Views and

the UNION operator can accept 1..N input sources.

Whereas a Script Based calculation view’s comparable CE_UNION_ALL function can

only accept 2 input sources at a given time.




You should now be able to:

Summary

Connecting Tables

Explain differences between Inner Join, Left Outer Join,

Right Outer Join, Full Outer Join, Text Join and

Referential Join when connecting tables.

Explain how using Standard Union and Union with

constant values.

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