Adabas Concepts of a Database for Mission-Critical Applications

Transcription

1 Adabas Concepts of a Database for Mission-Critical Applications Friedrich-Schiller-Universität Jena Lehrstuhl für Datenbanken und Informationssysteme Prof. Dr. Klaus Küspert February 1, 2011 Software AG Arno Zude, R&D ETS Adabas

2 Agenda 1) Software AG at a Glance 2) About the History of Adabas 3) Adabas Concepts Data Model Data Structures Recovery 4) Accessing Adabas 5) New Developments 6) Success Factors Feb 1, 2011 University of Jena 2

3 Software AG at a Glance Software AG at a Glance About the History of Adabas Adabas Concepts Founded in nd largest German software company Headquarters in Darmstadt 4th largest European software company Ca. 1.2 billion (10 9 ) revenue in 2010 Ca. 5,700 employees worldwide >2,000 in Germany ca. 850 in R&D Represented in 70 countries More than 10,000 enterprise customers Ca. 29% owned by Software AG Foundation Feb 1, 2011 University of Jena 3

4 Software AG at a Glance Software AG at a Glance Products About the History of Adabas Adabas Concepts 1st relational-like, transactional high-performance database One of the first 4 th -generation programming languages First Business-to-Business server and SOA integration platform First business process analysis & design platform Feb 1, 2011 University of Jena 4

5 Software AG at a Glance A Global Company R&D Labs in All Major IT Hotspots Software AG at a Glance About the History of Adabas Adabas Concepts Feb 1, 2011 University of Jena 5

6 About the History of Adabas About the History of Adabas Adabas Concepts Data Model Adaptable Database System Adabas development started in 1969 first on mainframe Relational-like, transactional, multi-user Used across all industries Banking, insurance, logistics, government, etc. More than 2,000 customers worldwide Developers in Germany, US, UK Darmstadt, Reston/VA, Denver/CO, Derby Runs on mainframes and open systems z/os, z/vse, z/vm, BS2000/OSD Unix, Linux (incl. z/linux), Windows Feb 1, 2011 University of Jena 6

7 Concepts Data Model Data Structures Adabas Concepts Data Model Adabas database Multiple files in a database Multiple records in a file Multiple fields in a record Linking different files via common fields no pointers between records like in relational model unlike in hierarchical, network models Database File Record Field Adabas vs. relational terminology: Read & update operate on individual records not sets of records Search operations create lists of record IDs not protected against parallel update Differences to relational model Adabas File Record Field Descriptor End Transaction Backout Transaction Relational Table Row Column Index Commit Rollback Feb 1, 2011 University of Jena 7

8 Concepts Data Model Data Structures Adabas Concepts Data Model II Various data types for fields Character, binary (Un)packed decimal numbers Fixed-point, floating-point Large objects (e.g., multi-media) Fields can be defined to have multiple values Multiple-value fields Groups of fields can be defined to have multiple occurrences Periodic groups Related data is kept close together Efficient data access Differences to relational model Feb 1, 2011 University of Jena 8

9 Concepts Data Model Data Structures Adabas Concepts Data Model III Fast read & search access via indexes called descriptors Several types of descriptors (Simple) descriptor One full field Subdescriptor Part of one field Superdescriptor Combination of parts of several fields Hyperdescriptor Combination of several fields Value(s) determined by user exit Collation descriptor Sort sequence defined by user exit Flexible, efficient data access Field = Jena Descriptor = Jena Field = Descriptor = 2011 Field 1 = Kuespert Field 2 = Descriptor = Kuespert Feb 1, 2011 University of Jena 9

10 Concepts Data Structures Recovery Adabas Concepts Data Structures Container datasets (disk files) Fixed block sizes, direct access Block = minimal I/O unit DATA Data storage The actual payload data ASSO Associator File directory Field definition tables Indexes Free space management WORK Work file for temporary use Journal of updates for restart recovery Search results PLOG Protection log Journal of updates for archive recovery Copied off for archival when full ASSO DATA FCBs File 1 FDTs File 2 Index 1 IX 2 Adabas Server WORK PLOG Seq. PLOG Feb 1, 2011 University of Jena 10

11 Concepts Data Structures Recovery Adabas Concepts Data Structures II Data Compression Field data typically stored in compressed form Character: No trailing blanks Numeric: No leading zeros Null-value suppression option Compact storage, efficient access Data storage (DS) Variable-length data records One or more records per block Record moved to other block if it becomes too large to fit Feb 1, 2011 University of Jena 11

12 Concepts Data Structures Recovery Adabas Concepts Data Structures III Address converter (AC) Each record identified by its ISN Internal Sequence Number A unique number, usually serial AC maps ISNs to DS blocks Index Index maps descriptor values to ISNs Stored as inverted lists B*-tree Feb 1, 2011 University of Jena 12

13 Concepts Data Structures Recovery Adabas Concepts Data Structures IV Finding data records from index via address converter to data storage: Feb 1, 2011 University of Jena 13

14 Concepts Recovery Accessing Adabas Adabas Concepts Recovery Restart recovery Performed if database server fails Power failure Canceled by operator System problem Software problem When server is restarted Protection data on WORK is used to detect need for restart recovery repair inconsistent internal data structures (e.g., index trees) redo committed updates that were not written out prior to the failure undo uncommitted updates that were written to the database Feb 1, 2011 University of Jena 14

15 Concepts Recovery Accessing Adabas Adabas Concepts Recovery II Archive recovery Performed if database gets damaged Disk failure Application misbehavior Software problem To repair damaged database or file(s) Restore archive copy of database/file(s) Use the protection data on the PLOGs to replay all updates performed between the time the archive copy was created and the time the damage occurred Alternative: Use the PLOGs to roll back all updates between the current time and the time first damage occurred Feb 1, 2011 University of Jena 15

16 Accessing Adabas New Developments Accessing Adabas Application programming interfaces to Adabas Direct call interface For example, from COBOL, C Natural (Software AG s 4GL) Adabas SQL Gateway ODBC JDBC Adabas SOA Gateway SOAP, REST Feb 1, 2011 University of Jena 16

17 Accessing Adabas New Developments Accessing Adabas Direct Call Interface Set up Adabas Control Block and up to five Adabas buffers with Adabas command to be executed Data to be searched, read, or inserted/updated/deleted Example (COBOL): MOVE 'S1' TO ADACB-COMMAND. MOVE 'I' TO ADACB-COP2. MOVE DBID-FNR TO ADACB-DBFILE. MOVE 'FIND' TO ADACB-CID. MOVE 'AA,8,A,AE,20,A,AJ1-3,20,A.' TO ADABAS-FORMAT-BUFFER. MOVE 'AE,9,A,D,AJ,5,A.' TO ADABAS-SEARCH-BUFFER. MOVE 'KUESPERT JENA ' TO ADABAS-VALUE-BUFFER. CALL 'ADABAS' USING ADABAS-CB, ADABAS-FORMAT-BUFFER, ADABAS-RECORD-BUFFER, ADABAS-SEARCH-BUFFER, ADABAS-VALUE-BUFFER, ADABAS-ISN-BUFFER. Feb 1, 2011 University of Jena 17

18 Accessing Adabas New Developments Accessing Adabas Natural is Software AG s 4 th -generation programming language for application development Example for calling Adabas: FIND PERSONNEL WITH NAME = ' KUESPERT' AND CITY = ' JENA' DISPLAY 'ID' PERSONNEL-ID 'Surname' NAME 'Location' CITY END-FIND Feb 1, 2011 University of Jena 18

19 Accessing Adabas New Developments Accessing Adabas Natural II Feb 1, 2011 University of Jena 19

20 Accessing Adabas New Developments Accessing Adabas SQL Gateway Adabas SQL Gateway Calling Adabas via an SQL interface SELECT personnel_id, name, city, FROM PERSONNEL t1, PERSONNEL_ADDRESS_LINE t2 WHERE name = 'Kuespert' AND city = 'Jena' AND t1.isn_personnel = t2.isn_personnel Executed by accessing only one Adabas file (table) PERSONNEL_ADDRESS_LINE is periodic group in PERSONNEL file Embedded into host programming language Calling Adabas via an ODBC or JDBC interface Feb 1, 2011 University of Jena 20

21 Accessing Adabas New Developments Accessing Adabas SOA Gateway Adabas SOA Gateway Calling Adabas via a request to a Web service URL Calling Adabas via a SOAP request Callable from programming languages, Web browser, Excel, Word, etc. Feb 1, 2011 University of Jena 21

22 New Developments Success Factors New Developments Application Java.NET 3GL Natural Administration Security Cross-platform SQL Java XML SOA Data Access Tamino XML Server Text Retrieval External e.g. RACF Availability Load Balancing Cluster Monitoring Statistics Utilities Performance Windows, Unix. Linux, Mainframe Data Management Replication Transaction Partitioning Save/Restore Data Organization Data Distribution VSAM DL/1 DB2 Apps Feb 1, 2011 University of Jena 22

23 New Developments Success Factors New Developments Adabas Cluster Services (2002) z/os A CF z/os B User XES Lock Cache XES User Adabas Server XCF Adabas Server DB DB WORK PLOG PLOG WORK Seq. PLOG Feb 1, 2011 University of Jena 23

24 New Developments Success Factors New Developments Event Replicator for Adabas (2005) Replication of production data RDBMS Close to real time From Adabas (source) To Adabas (destination) relational databases data warehouses applications JMS Messaging Database-to-Database Replication Data Warehouse Business Intelligence and Reporting Integration Platform Data Transformation, Enrichment and Routing Applications Multi-Target and Application Replication Feb 1, 2011 University of Jena 24

25 New Developments Success Factors New Developments Data Archiving for Adabas (2010) Archival of production data Business Applications Resource savings Automation Lower-cost hardware Regulatory compliance Storage Robust search capabilities Performance Relieve pressure on production database Recall X Extraction Filter Production Database Archive Database Archive Vaults/Files Archive Vaults Feb 1, 2011 University of Jena 25

26 New Developments Success Factors New Developments Data Masking for Adabas (2011) Generation of Test data production-like data for application testing end user training demonstration research Automated process Less resources to create test data Regulatory compliance Privacy Security Application quality Production versus generic data Sensitive Data Data Masking Data Masking Test Data Feb 1, 2011 University of Jena 26

27 Success Factors Success Factors Flexible data model Supports relational structures, entity-relationship model, others Excellent performance Key factor Helped by data model, record-level locking, exploitation of system functions Economical use of disk space via data compression, saving on I/O operations High availability Little downtime for maintenance (planned outages) Quick & reliable recovery (unplanned outages) Simple administration A few database administrators take care of many Adabas databases Several platforms Present across mainframes and open systems Feb 1, 2011 University of Jena 27

28 Adabas A database for mission-critical applications Feb 1, 2011 University of Jena 28