Teradata Parallel Transporter Scripts with Simplified Syntax

1. Teradata Parallel Transporter Scripts with Simplified Syntax Nam Tran, Teradata Parallel Transporter Teradata Corporation October 6, 2011

2. Today’s Agenda • Introduction • Job Script Example Before Simplified Syntax • Using Operator Templates • Using Generated Schemas • Using Generated SQL INSERT Statements • Job Script Example After Simplified Syntax • Q & A

3. Customer ease-of-use is of paramount importance to Teradata’s strategy. Teradata Parallel Transporter 13.10 and 14.0 introduces a simplified script syntax: Smaller and simpler job scripts Less job script maintenance with use of operator templates User-defined templates allow any degree of customization Generated schema objects Generated SQL insert statement Standardized the names of job variables that correspond to operator attributes Target audience of this presentation: Users of script-based TPT Users who write TPT job scripts Users who work with TPT job script generation tools Introduction

4. Declarative Section Defines the “what”: DEFINE SCHEMA object(s) DEFINE OPERATOR object(s) Job Script Example Before Simplified Syntax • Two main script sections DEFINE JOB File_Load DESCRIPTION ‘Load table from flat file’ ( DEFINE SCHEMA Customer_Accounts ( Account_Number INTEGER, Account_Name VARCHAR(50), Trans_Number INTEGER, Trans_Date ANSIDATE, Trans_Amount VARCHAR(20) ); DEFINE OPERATOR File_Reader TYPE DATACONNECTOR PRODUCER SCHEMA Customer_Accounts ATTRIBUTES ( VARCHAR FileName = @Filename, VARCHAR Format = @Format, VARCHAR OpenMode = @Openmode, VARCHAR TextDelimiter = @Delimiter, VARCHAR PrivateLogName = @DCLog ); /* continued on next page */

5. Executive Section Defines the “how” APPLY statement(s) Job Script Example Before Simplified Syntax (continued) /* continued from previous page */ DEFINE OPERATOR Load_Op TYPE LOAD SCHEMA * ATTRIBUTES ( VARCHAR TdpId = @TdpId, VARCHAR UserName = @UserName, VARCHAR UserPassword = @UserPW, VARCHAR TargetTable = @TarTable, VARCHAR LogTable = @LogTable, VARCHAR PrivateLogName = @LoadLog ); APPLY ‘INSERT INTO TABLE_X VALUES (:Account_Number, :Account_Name, :Trans_Number, :Trans_Date, :Trans_Amount);’ TO OPERATOR( Load_Op[2] ) SELECT * FROM OPERATOR( File_Reader ); );

6. Stores and specifies common operator attributes Reusable across multiple job scripts Job Variables File Tdpid = ‘drill’ ,Username = ‘johndoe’ ,Userpw = ‘janedoe’ ,TarTable = ‘TABLE_X’ ,LogTable = ‘TABLE_X_LOG’ ,LoadLog = ‘load.log’ ,Filename = ‘flatfile1.txt’ ,Format = ‘formatted’ ,Openmode = ‘read’ ,TextDelimiter = ‘|’ ,DCLog = ‘dc.log’

7. Defined as <name> = ‘value’ pair in ”-u” command line option, external job variables file, or in job script SET directive Once defined, @<name> can be used anywhere in job script to specify ‘value’ (except within quoted strings and comments) Most commonly used to assign values to operator attributes Script users are encouraged to use job variables for easier script maintenance. TPT simplified syntax will rely heavily on predefined job variable names Job Variables

8. Our goal? To make job scripts simpler by: Removing the declarative section Reusing common job variables Reducing potential keystroke errors DEFINE OPERATOR object: Using Operator Templates instead DEFINE SCHEMA object: Using Generated Schemas instead SQL INSERT statement: Using Generated SQL INSERT Statements instead Simplifying TPT Syntax

9. What are operator templates? Stored DEFINE OPERATOR statements for all TPT operators Uses formulaic names for the operators they define: $EXPORT, $LOAD, $UPDATE, $STREAM, etc. All possible operator attributes are declared Each operator attribute has a job variable reference as its value Standardizes job variable names that correspond to operator attributes Using Operator Templates

10. DEFINE OPERATOR $DDL DESCRIPTION 'Teradata Parallel Transporter DDL Operator' TYPE DDL ATTRIBUTES ( VARCHAR UserName = @TargetUserName, VARCHAR UserPassword = @TargetUserPassword, VARCHAR TdpId = @TargetTdpId, VARCHAR AccountId = @TargetAccountId, VARCHAR WorkingDatabase = @TargetWorkingDatabase, VARCHAR LogonMech = @TargetLogonMech, VARCHAR LogonMechData = @TargetLogonMechData, VARCHAR DataEncryption = @DDLDataEncryption, VARCHAR ARRAY ErrorList = @DDLErrorList, VARCHAR LogSQL = @DDLLogSQL, VARCHAR PrivateLogName = @DDLPrivateLogName, VARCHAR ARRAY QueryBandSessInfo = @DDLQueryBandSessInfo, VARCHAR ReplicationOverride = @DDLReplicationOverride, VARCHAR ARRAY TraceLevel = @DDLTraceLevel ); Operator Template Example

11. Templates are imported into the job script when operators are referenced in an APPLY statement using their template name, for example: APPLY ‘INSERT INTO TABLE_X (:col1, :col2);’ TO OPERATOR ($LOAD); By referencing the $LOADoperator template name, TPT knows to import the corresponding template Referencing Templates in Your Script

12. Templates contain predefined, conventionally-named job variables assigned to each operator attribute Assign predefined job variables as <name> = ‘value’ pair, for example: SourceUserName = ‘johndoe’ SourceUserPassword = ‘janedoe’ Unassigned job variables cause TPT to ignore value assignments Using Template Job Variables

13. For producer templates: Logon-associated: Source<AttributeName> VARCHAR UserName = @SourceUserName, VARCHAR UserPassword = @SourceUserPassword, VARCHAR TdpId = @SourceTdpId For consumer templates: Logon-associated: Target<AttributeName> VARCHAR UserName = @TargetUserName, VARCHAR UserPassword = @TargetUserPassword, VARCHAR TdpId = @TargetTdpId All other job variables names: <TemplateName><AttributeName> VARCHAR ARRAY ErrorList = @DDLErrorList, VARCHAR PrivateLogName = @DDLPrivateLogName Job Variables Naming Convention

14. Users can create their own templates to maximize usefulness: Template name must begin with ‘$’ and be unique Use SCHEMA * for consumer template and SCHEMA $ for producer template All operator attributes not assigned fixed values should be assigned predefined, conventionally-named job variables Store template in $TWB_ROOT/template directory User-Defined Templates

15. DEFINE OPERATOR $MY_DELIMITED_READER DESCRIPTION ‘My user-defined delimited file reader’ TYPE DATACONNECTOR PRODUCER SCHEMA $ ATTRIBUTES ( VARCHAR FileName = @SourceFileName, VARCHAR Format = ‘Delimited’, VARCHAR TextDelimiter = ‘,’, INTEGER IOBufferSize = @FileReaderIOBufferSize, : : : : VARCHAR PrivateLogName = @FileReaderPrivateLogName, VARCHAR TraceLevel = @FileReaderSkipRows, ); User-Defined Operator Template Example

16. All producer operators require a schema specification. How does TPT simplified syntax overcome this? Explicitly generated schemas A simpler way of defining a schema object via a DBS table name and allowing TPT to auto-generate the column definitions Inferred generated schemas A method by which TPT analyzes job step information to auto-generate a schema object and its column definitions Using Generated Schemas

17. Explicitly specify the name of a DBS table in DEFINE SCHEMA to: auto-generate a schema, for example: DEFINE SCHEMA WEEKLY_TRANSACTIONS ‘Weekly_Trans’; auto-generate a delimited-file schema, for example: DEFINE SCHEMA WEEKLY_TRANSACTIONS DELIMITED ‘Weekly_Trans’; Explicitly specify the name of a DBS table in the APPLY statement’s producer operator reference to: auto-generate a schema, for example: APPLY ‘INSERT INTO TABLE_X (:col1, :col2);’ TO OPERATOR ($LOAD); FROM OPERATOR ($EXPORT (‘TABLE_X’)); auto-generate a delimited-file schema, for example: APPLY ‘INSERT INTO TABLE_X (:col1, :col2);’ TO OPERATOR ($LOAD); FROM OPERATOR ($EXPORT (DELIMITED ‘TABLE_X’)); Explicitly Generated Schemas

18. What is an inferred schema? The schema of a producer template operator whose column content can be inferred from information in the same job step How does TPT infer a schema? By analyzing the script information of all operators invoked in any job step that employs one of more producer templates Inferred Generated Schemas

19. STEP LOAD_2 ( APPLY <DML statement> TO OPERATOR( $LOAD ) SELECT * FROM OPERATOR( $EXPORT ) UNION ALL SELECT * FROM OPERATOR( EXPORT_OP_2 ); ); Producer Operator $EXPORT: is an operator template instantiation does not have an explicit schema Producer Operator EXPORT_OP_2: is defined previously in the job script has a script-defined schema Source data from both producers is merged into a single input data stream Thus, TPT will “infer” the same schema for both operators Inferred Generated Schemas: Example 1

20. STEP INSERT_DAILY_TRANS ( APPLY <DML statement> TO OPERATOR( $LOAD ) SELECT * FROM OPERATOR( $SELECTOR ATTR( SelectStmt = ‘SELECT * FROM Daily_Trans;‘ )); ); Producer Operator $SELECTOR: is an operator template instantiation does not have an explicit schema The SelectStmt attribute has been assigned an SQL SELECT statement Thus, TPT will “infer” the schema based on the columns of the SELECT’s results table Works for producer templates $EXPORT and $SELECTOR, since both require the SelectStmt attribute Inferred Generated Schemas: Example 2

21. STEP INSERT_MONTHLY_SHIPMENTS ( APPLY <DML statement> TO OPERATOR( $LOAD ATTR( TargetTable = 'Monthly_Shipments‘ )) SELECT * FROM OPERATOR( $FILE_READER ); ); Consumer operator $LOAD: is an operator template instantiation has a TargetTable attribute assigned to ‘Monthly_Shipments’ Producer operator $FILE_READER: is an operator template instantiation does not have an explicit schema TPT will assume source data is loaded unchanged and “infer” the source schema based on the TargetTable Limitations: Assumption may not be correct in all cases, resulting in schema mismatch causing job to terminate TPT cannot infer a template’s schema from a target table when the job step contains multiple target tables Inferred Generated Schemas: Example 3

22. Whenever TPT generates a schema based on a DBS table, it must: Make a HELP TABLE call to DBS Construct DEFINE SCHEMA object Merge generated DEFINE SCHEMA object into job script Substitute generated schema for the SCHEMA $ in producer operator template How TPT Generates Schema

23. Generated schemas Major convenience when number of schema column definitions is large Reducing keyboarding time and keystroke errors TPT job scripts simpler, more compact, easier to read Limitations Requires the name of a DBS table that already exists prior to running the job Inferred schemas based on TargetTable attribute assumes data loaded unchanged Generated Schemas Advantages & Limitations

24. TPT supports one additional feature to reduce script size and eliminate keystroke errors: Generating any SQL INSERT statement: if the target table is specified or can be unambiguously determined For example: DBS table ’Invoice_Counts’ has 4 columns col1, col2, col3, and col4 By specifying: APPLY $INSERT 'Invoice_Counts' TO OPERATOR( $UPDATE ) SELECT * FROM OPERATOR( $SELECTOR ); TPT will replace $INSERT 'Invoice_Counts' with the following generated SQL INSERT statement: 'INSERT INTO Invoice_Counts VALUES ( :col1, :col2, :col3, :col4 );' Using Generated SQL INSERT Statements

25. Our Example Job Script – Simplified! After After Before Before DEFINE JOB File_Load DESCRIPTION ‘Load table from flat file’ ( DEFINE SCHEMA Customer_Accounts ( Account_Number INTEGER, Account_Name VARCHAR(50), Trans_Number INTEGER, Trans_Date ANSIDATE, Trans_Amount VARCHAR(20) ); DEFINE OPERATOR File_Reader TYPE DATACONNECTOR PRODUCER SCHEMA Customer_Accounts ATTRIBUTES ( VARCHAR FileName = @Filename, VARCHAR Format = @Format, VARCHAR OpenMode = @Openmode, VARCHAR TextDelimiter = @Delimiter, VARCHAR PrivateLogName = @DCLog ); /* continued on next page */ DEFINE JOB File_Load DESCRIPTION ‘Load table from flat file’ ( APPLY $INSERT TO OPERATOR( $LOAD[2] ) SELECT * FROM OPERATOR( $FILE_READER ); );

26. Our Example Job Script – Simplified! (continued) After After Before Before DEFINE JOB File_Load DESCRIPTION ‘Load table from flat file’ ( APPLY $INSERT TO OPERATOR( $LOAD[2] ) SELECT * FROM OPERATOR( $FILE_READER ); ); /* continued from previous page */ DEFINE OPERATOR Load_Op TYPE LOAD SCHEMA * ATTRIBUTES ( VARCHAR TdpId = @TdpId, VARCHAR UserName = @UserName, VARCHAR UserPassword = @UserPW, VARCHAR TargetTable = @TarTable, VARCHAR LogTable = @LogTable, VARCHAR PrivateLogName = @LoadLog ); APPLY ‘INSERT INTO TABLE_X VALUES (:Account_Number, :Account_Name, :Trans_Number, :Trans_Date, :Trans_Amount);’ TO OPERATOR( Load_Op[2] ) SELECT * FROM OPERATOR( File_Reader ); );

27. Job Variables Files Before After, with Conventionalized Names Tdpid = ‘drill’ ,Username = ‘johndoe’ ,Userpw = ‘janedoe’ ,TarTable = ‘TABLE_X’ ,LogTable = ‘TABLE_X_LOG’ ,LoadLog = ‘load.log’ Filename = ‘flatfile1.txt’ ,Format = ‘formatted’ ,Openmode = ‘read’ ,TextDelimiter = ‘|’ ,DCLog = ‘dc.log’ TargetTdpId = ‘drill’ ,TargetUserName = ‘johndoe’ ,TargetUserPassword = ‘janedoe’ ,LoadTargetTable = ‘TABLE_X’ ,LoadLogTable = ‘TABLE_X_LOG’ ,LoadPrivateLogName = ‘load.log’ ,FileReaderFileName = ‘flatfile1.txt’ ,FileReaderFormat = ‘formatted’ ,FileReaderOpenmode = ‘read’ ,FileReaderTextDelimiter = ‘|’ ,FileReaderPrivateLogName = ‘dc.log’

28. Q & A

29. Thank you!