Logical instruction of 8085
Instruction Set of 8085
Classification of Instruction Set
Logical Instructions
AND, OR, XOR
Logical Instructions
Summary Logical Group
Logical instruction of 8085
Instruction Set of 8085
Classification of Instruction Set
Logical Instructions
AND, OR, XOR
Logical Instructions
Summary Logical Group
Topic Overview:
Introduction to blogging and the state of the blogosphere
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How to make a blog that matters: Choosing your blogging platform, domain name, web hosting, genre, and style.
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Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
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Session Overview
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- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
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Send an interactive Slack channel message (using buttons)
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In a second workflow supporting the same use case, you’ll see:
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3. 1. AGGREGATOR TRANSFORMATION
A/C - AGG
DEFINITION
The Aggregator transformation is Active and Connected.
The Aggregator transformations allow you to perform to aggregate calculation.
You can use the aggregator transformation to perform calculation on groups.
The Row which meet the condition are passed to target.
The doesn’t meet the condition, rejected row store rejected file or Bad file directory.
AGGREGATOR FUNCTIONS
AVG MAX STDDEV
COUNT MEDIAN SUM
FIRST MIN VARIANCE
LAST PERCENTILE
PORTS
INPORTS - (I) each input Receive data
OUTPORTS - (O) Pass the data to other transformation
VRIABLE PORTS - (V) its stores the Intermediate result it can reference input ports
Not to out ports
GROUP BY PORT -
PROPERTIES
Cache Directory - $PMCaheDir
Tracing Level - Normal ( Terse / Normal / Verbose initialization /
verbose data )
Sorted Input -
Aggregator Data Cache - 2000000 Bytes
Aggregator Index Cache - 1000000 Bytes
Transformation Scope - All input (Transaction / All Input)
COMPONENT
Aggregate Expression - Non aggregate Expression / Conditional Class
Aggregate Cache -
Group by Port - Which column you want group by Eg. Dept
Sorted Input - Reduce the amount of data cached
AGGREGATOR CACHE:
The PCS stores data in the aggregate cache until it complete the aggregator calculation
Index Cache : It stores the group value, As Configured in the group by port
Data Cache : Stores calculation ( Row data Stores, output value) Based on group-by-ports
OPTIMIZATION
− Group by simple columns like numbers instead of string or date
− Use sorted input
− Use incremental aggregation
− Minimize the aggregate function
− Before filter transformation best ( Reduce the Data)
− Lookup unconnected & stored procedure – we can call
M.SHANMUGAM Transformation Details Page 3 / 24
4. 2. EXPRESSION TRANSFORMATION
P/C - EXP
DEFINITION
Expression Transformation Passive and connected transformation
This can be calculate values in a single row before writing to the target.
Row by row calculation,
Perform the any non aggregate function
EXPRESSION FUNCTIONS
The Expression Transformation is used for data cleansing and scrubbing
There are over 80 functions within PowerCenter, such as salary, concatenate, instring, rpad,
ltrim and we use many of them in the Expression Transformation.
We can also create derived columns and variables in the Expression Transformation.
COMPONENT
Expression - we can call – Unconnected Stored Procedure and Unconnected Lookup
PORTS
INPORTS - (I) Each input port Receive data
OUTPORTS - (O) which provide the value to either target or next transformation
in the mapping is called output ports
VARIABLE PORTS - (V) Its stores the Intermediate result it can reference input ports
( -Which stores the variable information )
PROPERTIES
Tracing Level - Normal ( Terse / Normal / Verbose initialization /
verbose data )
OPTIMIZATION
− Factoring out common logic
− Minimizing aggregator function calls. For Eg.use SUM(A+B) instead of using SUM(A) +
SUM(B)
− Replacing common sub expression with local variables
− Choosing Numeric Vs String operation
− Choose DECODE function Vs LOOK UP operation
− Choose CONCAT operation for Eg use ||’|| instead of CONCAT (Fname, Lastname)
− you can enter multiple expression in a Single Expression Transformation.
M.SHANMUGAM Transformation Details Page 4 / 24
5. 3. FILTER TRANSFORMATION
A/C - FIL
DEFINITION
− This is a type of active and connected Transformation which is used to filter of the source rows
based on a condition.
− Only the row which meet the condition are pass through to target.
− Any kind of source we can use filter Transformation
− Filter condition drops data that does not match the condition
− We can put one or more condition (more condition means we can use AND , OR operator)
− Discards rows don’t appear in the session log or reject files
PORTS
INPORTS - (I) Receive data from source
OUTPORTS - (O) Pass the data to other Transformation
PROPERTIES
Filter Condition : <put Condition>
Tracing Level : Normal (Normal / Terse / Verbose init / Verbose data )
OPTIMIZATION (TIPS)
♦ Use the filter transformation early in the mapping (or) nearly in SQ
♦ The filter condition is case sensitive, and queries in some database do not take this into
account.
TROUBLESHOOTING
Case sensitivity : the filter condition is case sensitive
Appended spaces : use the RTRIM function to remove additional space
FUNCTIONS
- You can use one or more condition in filter transformation
- AND , OR logical operator through
M.SHANMUGAM Transformation Details Page 5 / 24
6. 4. JOINER TRANSFORMATION
A/C - JNR
DEFINITION
- This is active and connected Transformation.
- Can be used to join two sources coming form two different locations or same location.
- We can use homo genius and hetero genius sources
- Join a flat file and a relational sources or to join two flat files or to join a relational source
and a XML source.
CONDITION
1). Two sources there must be at least one matching ports or columns
2). Two sources there should have Primary key and Foreign key relationship
PORTS
INPORTS - (I) Receive data from source
OUTPORTS - (O) Pass the data to other Transformation
MASTERPORTS - (M) If checked master(small) otherwise details (large)
(to switch the Master Details relationship for the source )
PROPERTIES
1 Cache sensitive String Comparison - (Character data only enable)
2 Cache Directory - $PMCacheDir
3 Join Condition -
4 Join Type - NORMAL (Normal - M.outer -D.outer- Full Outer)
5 Null ordering in Master - Null is highest value (Null is lowest value)
6 Null ordering in Detail - Null is highest value (Null is lowest value)
7 Tracing Level - Normal (Normal / Terse / Verbose init / Verbose data )
8 Joiner Data cache size - 2000000
9 Joiner Index cache size - 1000000
10 Sorted Input -
11 Transformation Scope - All input (Transaction / All Input )
COMPONENT
Case sensitive string comparison - (Character data only enable)
Cache directory -
Join condition -
Joiner type - ( Normal, Master Outer, Detail Outer, Full outer)
CACHE
Joiner Data cache size : Out put value only
Joiner Index cache size : The index cache holds rows from the master source that are in
the join condition.
M.SHANMUGAM Transformation Details Page 6 / 24
7. Index cache Data Cache
Stores index values for the master source table as Stores master source rows.
configured in the join condition.
FUNCTIONS
Following types of source can be used in a joiner
− Two relational tables existing in separate databases
− Two flat files in potentially different file systems
− Two different ODBC sources
− Two instances of the same XML sources
− A relational table and a Flat file source
− A relational table and a XML source
A joiner cannot contain the following types of source
− Both pipelines begin with the same original data sources.
− Both input pipeline originate from the same source qualifier transformation
− Both input pipeline originate from the same normalizer transformation.
− Both input pipeline originate from the same joiner transformation.
− Either input pipeline contains an update strategy transformations
− Either input pipeline contains a connected or unconnected sequence Generator transformation.
PERFORMANCE
− Use sorted input (flat file ,relational data,)
− Minimizing the disk input and output
− Use in front of sorted transformation
− For an unsorted joiner transformation, designate as the master source the source with fewer rows
− For an sorted joiner transformation, designate as the master source the source with fewer duplicate key
values
− Following Transformation we can’t use before the joiner Transformation.
- Sequence Generator Transformation directly
- Update strategy Transformation
TIPS
- sorted input – improve the session performance.
- Don’t use following transformation sort origin and joiner transformation
- Custom , Unsorted aggregator, Normalizer, Rank.
- Sort order from both table( master & Detail)
- Normal or Master outer join perform than a full outer or detail outer join.
Normal - Matched Rows form master and detail source
Master - all rows data from the detail source and the matching rows from the master source
Detail - all rows data from the master source and the matching rows from the detail source
Full outer - all rows rows of data from both the master and detail sources
M.SHANMUGAM Transformation Details Page 7 / 24
8. 5. RANK TRANSFORMATION
A/C - RNK
DEFINITION
This an Active and Connected Transformation
Which is used to identify the Top or Bottom rank of data based on condition.
Rank transformation to return the largest or smallest numeric value in a port or group
We can use a rank transformation to return the strings at the top or the bottom of a session
sort order.
FUNCTIONS
ASCII - Binary sort order
UNICODE - Session sort order in session properties (code Page)
Binary sort order
Binary value string and returns rows with the highest binary values for string
PORTS
INPUT ( I) - minimum of one
OUTPUT (O) - minimum of one
VARIABLE (V) - Stores values or calculations to use in an expressions
RANK (R) - Only one (default port-only out put return only)
EXPRESSION -
GROUP BY PORT -
PROPERTIES
CACHE DIRECTORY - $PMCacheDir
TOP / BOTTOM - TOP
NUMBER OF RANKS -
CASE SENSITIVE STING COMPARISON -
TRACING LEVEL - normal
RANK DATA CACHE SIZE - 2000000
RANK INDEX CACHE SIZE - 1000000
TRANSFORMATION SCOPE - All input (All input/ Transformation)
CACHE
Index Cache Data Cache
Stores group values as configured in the Stores ranking information based on the group
group by ports. by ports.
Can must run the session on a 64bit PoweCen
PERFORMANCE
- Configure ASCII mode
M.SHANMUGAM Transformation Details Page 8 / 24
9. 6. SORTER TRANSFORMATION
A/C - SRT
DEFINITION
♦ It allows to sort data either in ascending or descending according to a specify sort key (field)
♦ Also used to configure for case- sensitive sorting and specify whether the output rows should
be distinct.
FUNCTIONS
- Sort data from relational or flat file source.
- The sorter transformation treats the data passing through each successive sort key port as a
Secondary sort of the previous port.
COMPONENT
DIRECTION (V) - Ascending or Descending
PORTS
INPORTS (I) - Receive data from source
OUTPORTS (O) - Pass the data to other Transformation
KEY (V) - Which one u want to sort the A/D)
PROPERTIES
Sorter cache size :10000000 #input rows + [ (∑column size) + 16]
Case sensitive : (enable)Uppercase higher than lower case
Work directory : #PMTempDir (Temp file store-sorting time
Distinct : enable– eliminate duplicate value in out put
Tracing level : normal ( Terse / Normal / Verb init / Verb data )
Null treated low : (enable–treat null values higher than any other value)
Transformation scope :All input 1) Transaction 2) All Input
SORT DATA
Each successive sort key port as a secondary sort of the previous port
FORMULA
# input rows [( Σ column size ) + 16]
PERFORMANCE
- Sorter transformation to sort data passing through an Aggregator transformation configured to use
sorted transformation
- You should configure sort criteria to PCS applies to all sort key ports
M.SHANMUGAM Transformation Details Page 9 / 24
10. 7. SOURCE QUALIFIER TRANSFORMATION
A/C - SQ
DEFINITION
When adding a relational or flat file source definition to a mapping it is must to connect it to a
Source Qualifier Transformation.
The Source Qualifier transformation represents the rows that the powerCenter server reads when
it runs a session.
FUNCTIONS & Perform
Overriding the default SQL query - Only relational
Filtering the record - Only relational
Join the data from two or more tables etc, - Same source database
IMPORTANT TOPIC
Target load order - Constraint based load
Parameter & variable - $$$ session start time
Default query -
SQL Overwrite -
Override the default SQL query (user defined join, source filter, no of sorted ports, select distinct
setting
PORTS
INPORTS (I) - Receive data from source
OUTPORTS (O) - Pass the data to other Transformation
PROPERTIES
SQL Query - (custom query replace the default query)
User Defined join - (user defined join)
Source filter - (filter condition)
No of Sorted ports - 0 (order by includes no of ports-sort order)
Tracing level - normal ( Terse / Normal / Verb init / Verb data )
Select Distinct - (enable-unique values from source) only enable flat file
Pre SQL - (before reads to the source)
Post SQL - (after it writes to the target)
OPTIMIZATION
- Use the source qualifier to filer. The source qualifier limits the row set extracted from the source where
as filter limits the row set sent to a target.
PERFORMANCE
- Join data originating from the same source database
- Filter rows when the PCS reads source data
- Specify an outer rather than the default inner join
- Specify sorted ports
- Select only distinct values from the source
- Create custom query to issue a special select statement for the PCS to read source data
- Data type we can’t change, if you can change mapping is invalid.
Target Load Order:
- Multiple SQ connected multiple target.
- One SQL provide multiple target you can enable constraint based loading in a session to have the
PCS load data based on target table PK & FK relationship.
Default Join:
- PK – FK Relationship
- Matching Data Type
Custom Join:
- Custom don’t have PK & FK relationship
- Data type of columns used for the join don’t match
Outer Join support :
- Default query outer join statement nested query created -( left outer, right outer, full outer)
M.SHANMUGAM Transformation Details Page 10 / 24
11. 8. ROUTER TRANSFORMATION
A/C - RTR
DEFINITION
- This is an active and connected Transformation
- Similar to Filter Transformation
- Single input multiple Target opp to union Transformation.
- Processing the incoming data only once and passes the output to multiple groups and routes data to
the default O/P group that do not meet the condition
FUNCTIONS
- Router Transformation in a mapping the PCS process the incoming data only once.
- Router Transformation efficient of Filter Transformation
- Router Transformation one input group multiple output group
(user define output group (many) & default output group (one only)
PORTS
Input Port - (enable ) only input group
Output Port - (not visible) - only output group ( because group only findout)
GROUP
Input group - user define group to test a condition based on incoming data
Output group - 1. user defined group
2. Default group
- we can’t modify on delete output ports
- only connected target group
- out put group of sequential only default created.
- If you want the PCS to drop all rows in the default group, don’t connect it to a
transformation or a Target in a mapping.
- If rows meet more then one group filter condition, the PCS Passes this rows multiple time
PROPERTIES
Tracing Level -
COMPONENT
Input and Output groups
Input and Output ports
Group filter conditions
PERFORMANCE &TIPS
- One group can be connected to more then one transformation or target
- One output ports in a group can be connected to multiple transformation or targets.
- Multiple output ports in one group can be connected to multiple transformations or targets
- More than one group cannot be connected to one transformation or target
- We can’t connect more then one group to multiple input group Transformation, except for joiner
transformations, when you connect each output group to different input group.
M.SHANMUGAM Transformation Details Page 11 / 24
12. 9. SEQUENCE GENERATOR TRANSFORMATION
P/C - SEG
DEFINITION
Sequence Generator Transformation generates the numeric values.
SGT to create unique primary key values, cycle through a sequential range of numbers
Common Use: - SG when you perform multiple loads to a single target
- Replacing the missing values.
We can’t connect to more then one transformation
FUNCTIONS
CURRVAL - NEXTVAL + INCREMENTAL BY VALUE
One row in each block
Currval port without connecting the nextval port
PowerCenter server passes a constant value for each row
One row in each block
NEXTVAL - primary key – down stream transformation
Unique PK values formation to generate the sequential based on the current value
PORTS ( Both are default port )
INPORTS - Receive data through unconnected Transformation
OUTPORTS - Pass the data to other transformation
- 2 Default output ports 1. NEXTVAL , 2. CURVAL
PROPERTIES
Start value - 0 cycle option (enter the value complete the cycle value after restart the
value
Increment by - 1 D b/w 2 consecutive values from the nextval port the default values is 1
End value - (1-2147483647) the maximum values powerCenter generates.
- sequence is not configured to cycle it fails the session.
Current value- enter you want first value PC server to use in sequence
-must be generate than or equal to the start value and less than the end
value.
Cycle - If selected –sequence range (up to limit)
- If not selected – session failure with overflow error.
Number of cached values –1 no of cached values determine the number of values the PC
server caches at one time
Reset - If selected, PC generates values based on the original current value for each
session (other wise)
Reflect the last – generated value
(Reusable is disabled for reusable sequence generator Transformati
Tracing level - level of information
PERFORMANCE
NON REUSABLE SEQUENCE GENERATOR
Cache enable limit grater than 0.
- row skipped the value.
- discards the unused values.
REUSABLE SEQUENCE GENERATOR
-Cache enable some upto limit Eg.1000
OPTIMIZATION
− Use reusable sequence generator if the same sequence generator is to be used in more than one sessions.
− Optimize performance by connecting only the nextval port in a mapping
− Sequential reusable and use it in multiple mapping.
M.SHANMUGAM Transformation Details Page 12 / 24
13. FUNCTIONS
- Perform the following task with a sequence generator Transformation
- Create keys
- Replace missing the value
- Cycle through a sequential range of numbers
M.SHANMUGAM Transformation Details Page 13 / 24
14. 10. UPDATE STRATEGY TRANSFORMATION
A/C - UPD
DEFINITION
This is an active and connected transformation.
It is used to update in data in target table, either to maintain history of data or recent changes
It is used to flag the records for Insert, update, Delete and Reject rows in the Target database.
It is used in slowly changing dimension to update the target table.
This transformation used to SCD-1,SCD-2 and SCD-3 type.
FUNCTIONS
Set at a 2 levels
1. Within a session – treat all records in the same way
for example, treat all records as
DD_INSERT-0,DD_UPDATE-1,DD_DELETE-2,DD_REJECT-3,
2. Within a Mapping Levels – Flag records for insert, update, delete or reject
• Insert. Select this option to insert a row into a target table.
• Delete. Select this option to delete a row from a table.
• Update. You have the following options in this situation:
Update as update. Update each row flagged for update if it exists in the target table.
Update as insert. Inset each row flagged for update.
Update else Insert. Update the row if it exists. Otherwise, insert it.
• Truncate table. Select this option to truncate the target table before loading data.
PORTS
INPORTS (I) - Receive data from source
OUTPORTS (O) - Pass the data to other Transformation
PROPERTIES
Update strategy expression -0 (DD_INSERT-0,DD_UPDATE-1,DD_DELETE-2,DD_REJECT-3,)
Forward rejected rows - enable - flags the rows for reject and writes them to the session reject file.
Tracing level - normal ( Terse / Normal / Verb init / Verb data )
FUNCTION
SCD-1 : It keeps the most recent updated values in the target
SCD-2 : It keeps the full historical business information in the target
The full history is maintain by inserting the new record in the target
SCD-3 : It keeps previous value and current
PERFORMANCE
1. Whenever use Dynamic cache - at the time you must use UPD transformation
2. Dynamic lookup use you can must select
1. Select insert 2. select update as update 3. Don’t select delete
3. UPD - > AGG Use only – Update , Insert , Delete
4. AGG - > UPD Use only – Update , Insert , Delete, Reject
UPDATE STRATEGY
Dynamic lookup – u must use UPD transformation
Business Logic :
IFF((current date>Previousdate) , DD_reject, DD_update)
Update, Insert , Delete
UPD AGG
Update, Insert , Delete , Reject
AGG UPD
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15. - Dynamic lookup use you can must select
- Select Insert
- Select Update as update
- Don’t select delete
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16. 11. LOOKUP TRANSFORMATION
P/C & UC - LKP
DEFINITION
Look up Transformation in lookup data in flat file or a relational table, view or synonym
Get a related value
Look up transformation is used to perform the following task.
Get a related value
Perform a calculation
Update slowly changing dimension
FUNCTIONS
Relational look up - dynamic cache use
Flat file lookup - must use in static cache
- we can configure sorted input
PORTS
INPUT ( I) -
OUTPUT (O) -
LOOKUP (L) -
RETURN (R) -
PROPERTIES
Look up SQL Override (R) -
Lookup table name (R) -
Lookup caching enabled (R/F) -
Lookup policy on multiple match ”-
Lookup condition -
Location information -
Source type -
Re cache if stale
Tracing level
Lookup cache directory name
Lookup cache initialize
COMPONENT
Look up table
Ports
Properties
Condition
Metadata Extensions
LOOK UP CACHE
Persistent cache
Re cache from database
Static cache
Dynamic cache
Shared cache
PERFORMANCE
Cached lookup:By indexing the columns in the lookup Order by
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17. LOOK UP TRANSFORMATION
Look up
To look up data in Flat File, Table, Synonym, View.
Use multiple lookup transformation in a mapping
Performs the following tasks
Get related value
Perform calculations
Updated slowly changing dimension tables.
Connected Lookup
Static cache : return value from the lookup query.
Dynamic cache : Case 1 : No rows found in cache – inserts the record
Case 2 : Row found in cache - updates the records
Unconnected Lookup
- Common use into update slowly changing dimension – tables
- Returns one value into the return port of look up transformation
Connected or Unconnected
- Receive input and send output in different ways
Relational or flat file lookup
Cached or uncached
Dynamic - Relational
Static - Flat file
Cached - Performance ( store the value whenever you want lookup table refer only
Uncached - each time lookup the value.
Connected Lookup Transformation
Unconnected Lookup Transformation
Relational & flat files lookups
Relational Lookups - Dynamic cache
Flat file lookup - Can use sorted input
- Can use indirect file
- Can sort null date high
- Can use case sensitive string comparison
LOOK UP COMPONENTS
Look source - cached lookup – order by
Ports - Uncached lookup – select
Properties -
Conddtion -
PORTS
INPUT PORT (I) -
OUT PORT (O) -
LOOKUP (L) -
RETURN (R) - only in connected lookup transformation
PROPERTIES
Lookup SQL override (R) -
Lookup table name (R) - Table, Synonym, View
Lookup caching enabled (R/F) -
Lookup policy on multiple match (F/R)- enable mean (first, last, return an error)
Look Condition (F/R) -
Connection information (R) -
Source Type (R/F) -
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18. Tracing Level (R/F) -
Lookup cache Directory name (F/R) -
Lookup cache Persistent (F/R) -
Look up Data cache size (F/R) -
Look up index cache size (F/R) -
Dynamic lookup cache (R) - insert (or) updates – (only lookup cache enabled)
Output old value on update (F/R) - use only with dynamic cache enabled
Cache file name prefix (F/R) - use only with persistent lookup cache
- name prefix to use persistent lookup cache file
Re cache from lookup source(F/R) - Rebuild the persistent cache file
Insert else update (R) - use only with dynamic cache enabled
Update else Insert (R) - ”
Date Time format (F) -
Thousand separator (F) - default no separator (‘,’ ‘.’)
Decimal separator (F) - default period (, .)
Case sensitive string comparison(F) -
Null ordering (F) -
Sorted Input (F) -
Configuring Lookup Properties in a Session
Flat file lookups - (file name and file type)
Relational Lookup - (u can define $source & $Target variable in session)
Configuring Properties Flat file Lookup in a Session
Lookup source file directory - $LookupFileDir (default)
Lookup source file name -
Lookup source file name - Direct
Configuration Relational Lookups in a Session
Choose any relational connection
Connection variable , $DBconnection
Specify database connection for $Source and $Target
Lookup Query
Default lookup query
• SELECT - SQL override
• ORDER BY - we can use enabled the cache ( u can’t view this )
Overriding the lookup Query
• override the ORDER BY statement
• A lookup table name(or) columns contain a reserved word - 'reserved word’
• Use mapping parameter & variables
• A Lookup column name contains a slash (/) character
• Add where statement
• Other
Overriding the ORDER BY Statement
Order by - -
Reserved words
- lookup or column names contain a database reserved word
such as Month,Year – session fails
- resword.txt (PC initialization Directory)
Guideline to Overriding the Lookup Query
- SQL override only lookup SQL query relational only
- Cache not enable PCS doesn’t recognize the override
- Default query or configure override – lookup / output port – add or subtract port from the
SELECT statement, the session fails,
- Filter before lookup using dynamic cache when you add where clause to lookup SQL override
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19. -Override the ORDER BY statement – session fail (because doesn’t contain condition port)
Don’t suppress order only
- Reserved word session fail if you want use quotes ( “ ”)
Step overriding the Lookup Query
Properties Tab enter SQL override
Validate to test
Lookup condition
1 . Data type in condition must match
2. Multiple condition – use AND, OR
3. Flat file for sorted input – session fail (condition are not grouped so you select group column)
Uncached Static cache
1. =, >, <, >=, <= , !=
2. multiple condition – use AND , OR
3. more then one lookup condition (first meet all condition after another condition so you select
GROUP columns
Dynamic cache
1. Only = operator
2. can’t handling for multiple matches – otherwise PCS fail
Lookup Cache
Index cache - Condition value
Data cache - Output value
1). Persistent cache -
2). Recache from lookup source -
3). Static cache -
4). Dynamic cache -
5). Shard cache -
Configuring Unconnected Lookup Transformation
- :LKP – reference qualifier to call the lookup within another transformation
- Calling the same lookup multiple time in one mapping
- Syntax: :LKP.Lookup_transformation_name(argument,argument,…..)
Unconnected use following kinds.
- Add input port - more then one condition
- Add the lookup condition
- Designate a return value
- Call the lookup from another transformation
Add input port
Design for source and target
Item_id out
IN_Item_id in
Add Lookup Condition
Item_id = IN_Item_id
- return condition is false lookup return null
Designate a return value
- Multiple input & single output only
- Update strategy or filter expression
Call the lookup through an Expression
Eg. IFF(Isnull(:LKP.lkpitems_dim(item_id,price)),DD_Update,DD_Reject
Creating a Look Transformation
1. Choose an existing table or file definition
2. Import a definition from a relational or file
3. skip a create a manual definition
TIPs
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20. 1. Add an index to the column used in a lookup condition
2. place condition with an equality operator(=)first
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21. LOOKUP CACHE
Index - PCS Condition value
Data Cache - Output Value
Default - $PMCacheDir
- Data doesn’t fit in the memory cache
- PCS stores the overflow value in the cache file when the session complete
- Flat file lookup for sorted input
1. Persistent Cache :
- Save and reuse them the next time
2. Recache from source
- persistent cache is not synchronized with the lookup table
- Rebuild
3. Static Cache
- Read only
- Default cache
- PCS doesn’t update the cache
4. Dynamic Cache
- insert new rows or update existing row
- Dynamic insert & update – pass data to target table
- Can’t use flat file
5. Shared Cache
- use can use multiple transformation
1. PERSISTENT CACHE :
- PCS save or delete lookup cache files after successful session based on the lookup cache
persistent property.
- Lookup table doesn’t change between session you can configure the lookup transformation to
use a persistent lookup cache.
- PCS saves & reuses cache files from session to session so eliminating time required to read the
lookup table.
Non Persistent Cache
- Enable caching in lookup transformation the PCS delete the cache files at the end of a session
- Next time you run the session the PCS build the memory cache from the database.
Persistent cache
- If you want save and reuse the cache files you can configure the transformation
- Use persistent cache the lookup table doesn’t change between session runs
- Lookup table changes occasionally, can override session properties to re caches the lookup from
the database
- Use Persistent cache means you can specify a name for the cache file
PCS server handling of persistent caches
2. REBUILDING THE LOOKUP CACHES
- Rebuild the Lookup caches, lookup sources changed size the last time the PCS build the cache
- When you rebuild the cache the PCS create new cache file overriding existing persistent cache
file
- The PCS server write a message to the session log file when if rebuild the caches
- Don’t choose the to recache the lookup source PCS automatically rebuild the persistent cache
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22. 3. STATIC CACHE (or) UCACHED LOOKUP
- The PCS builds the cache when it process the first lookup request
- PCS doesn’t update the cache.
- Condition true – connected lookup transformation return values represent by lookup/output
ports.
- Condition true - unconnected lookup transformation return values represent by return ports.
- Condition is not true – connected lookup transformation return values to output port.
- Condition is not true – unconnected lookup transformation return null values to returns port.
- Multiple partition means PCS create one memory cache for each partition .
4. DYNAMIC LOOKUP CACHE
- Insert the row into the cache
- Update the row in the cache
- Makes no changes to the cache
- Some situation when you can use dynamic lookup cache
1. Update a master customer table with new & updated customer information
- Static lookup cache - fact file
- Dynamic lookup cache - Relational table
2. Loading data into a slowly changing dimension table & a fact table
3. Router or filter - use
4. Multiple partition in a pipeline that use a dynamic lookup cache the PCS create one me
memory cache and one disk cache for each transformation .
New lookup row port
- Target table synchronized
- Ignore Null input for updates
- Ignore in comparison
• Ignore Null values
Using the Associated Input port :
- You must associated each lookup/out port with an input/output port or a sequence ID
- The PCS uses the data in the associated port to insert or update rows in the lookup cache.
Sequence ID Generate following Process
- PCS create dynamic lookup cache – tracks the range of value in the cache associated with
any port using a sequence ID
- Maximum value for a sequence ID is 2147483647.
Working with lookup Transformation values
- Associated an input/output ports or a sequence ID with a Lookup/output port – following
Value match default.
• Input Value - PCS passes into the Transformation
• Lookup Values - PCS Passes insert into the cache.
Input /output port output value – PCS Passes out of the Input/output port
- Out put old value on update – PCS output the value that existed in the cache before it
updated the row.
- Out put new value on update – PCS output the updated value that it write in the cache
- When the update a dynamic lookup cache & Target table.
- PCS can handle the null values in the following ways.
• Insert Null values -
• Ignore Null values - (Not null values)
- When you run a session that use a dynamic lookup cache PCS compares the value in all
lookup ports with the value.
- If compare the value to determine whether or not to update the row in the lookup cache.
Update strategy Transformation with a Dynamic chache.
1. Row entering the lookup Transformation : (By default) all row type all rows entering a
lookup transformation is insert.
2. Row Leaving the Lookup Transformation : PCS changed the lookup cache but it does not
change the row type
- Update Strategy transformation & a dynamic lookup cache you must define certain
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23. session properties
- PCS result the lookup cache & Target table might become unsynchronized.
5. SHARING THE LOOKUP CACHE
- You can configure multiple lookup Transformation in a mapping to store a single lookup
cache.
- You can share cache that are unnamed & named.
1. Unnamed Cache: - Compatible caching structure
- The PCS share the cache by default you can share static unnamed
caches.
2. Named Cache : - Use a persistent named cache
- when you want to share cache files across mapping or share and a static
cache
Sharing an Unnamed Lookup cache :
- When 2 Lookup transformation share an unnamed cahce.
- You can share static unnamed cache.
Sharing a Named Lookup Cache.
- We can share the cache between multiple lookup transformation by using a Persistent
- We can share one cache between lookup Transformation is the same mapping (or) across
mapping
- Named cache – cache directory for cache files with the same files name prefix.
- Specify the cache file directory.
- PCS rebuild the memory cache from the persisted file
- PCS structure don’t match the PCS fails the session.
- PCS process multiple session simultaneously when the lookup transformation only need
to read the cache files.
- A named cache created by a dynamic lookup transformation with a lookup policy
TIPs
- PCS then saves & reuses cache files from session to session, eliminating the time
required to read the lookup table
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24. 14. UNION TRANSFORMATION
A/C - UN
DEFINITION
- Union Transformation is a multiple input group transformation which is responsible for merging the
data coming from more then one source.
- Union Transformation also merge the data Hetero geneous sources also.
- Union Transformation is newly introduced in Informatica 7.1 version onwards.
- Union Transformation to the UNION ALL statement
- Union Transformation is developed using the custom Transformation.
FUNCTIONS
- Create Multiple input groups but only one output groups
- All Input groups and the out put groups must have matching port. The precision, data type, and scale
must be identical across all groups
- Union Transformation doesn’t remove duplicate rows.
- To remove duplicate rows you must add another transformation upstream from a union Transformation.
- Can’t use sequence generator or update strategy transformation upstream from a Union Transformation.
- Union Transformation doesn’t generate transaction.
COMPONENT
Transformation Tab : you can rename the transformation and add a description
Properties Tab : you can specify the Tracing level
Groups : you can create & delete input groups (Design displays groups you create
on the ports tab
Groups ports tab : you can create & delete ports for the input groups
We can’t modify ports, Initialization properties, meta data Extension or port attributes definition Tab
PORTS
Groups & ports :
Multiple input groups & one output groups, Design create output groups by default we can’t edit
or delete the outputs groups
MAPPING
- Union Transformation is a non blocking multiple input group Transformation
- When you add a Union Transformation to a mapping you must verify that you connect the same ports in
all inputs groups. If you connect all ports in one input group but don’t connect a port in another input
groups. If you connect all ports in one input groups, but don’t connect a port in another input group the
PCS passes Nulls to the unconnected ports
PROPERTIES
Mapping level - Session Level
Module identifies - Pmuniontrans
Function identifiers - pmunionfunc
Runtime Location - enable
Tracing Level - Normal enable
Is Partition able -
Inputs Must Block -
Is Active -
Update Strategy Transfomat -
Transformation Scope - Row
Generate Transformation -
Output Repeatable - Never
PERFORMANCE
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