Automating Information Lifecycle Management with

Transcription

1 Automating Information Lifecycle Management with Oracle Database 2c

2 The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle s products remains at the sole discretion of Oracle. 2 Copyright 23, Oracle and/or its affiliates. All rights reserved.

3 Agenda Data Growth Heat Map Automatic Data Optimization Benefits of Heat Map and ADO 3 Copyright 23, Oracle and/or its affiliates. All rights reserved.

4 Growth in Data Diversity and Usage,8 Exabytes of Data in 2, 2x Growth by 22 Today s Drivers Emerging Growth Factors Enterprise 45% per year growth in database data Cloud 8% of new applications and their data Regulation 3 exabytes in archives by 25 Mobile # Internet access device in 23 Big Data Large customers top 5PB Social Business $3B/year in commerce by 25 4 Copyright 23, Oracle and/or its affiliates. All rights reserved.

5 Managing Storage Challenges Manage more data without incurring additional cost Compress data, without impacting performance Tier and compress data based on usage 5 Copyright 23, Oracle and/or its affiliates. All rights reserved.

6 Data Compression Reduce storage footprint, read compressed data faster Hot Data 3X Advanced Row Compression Warm Data X Columnar Query Compression Archive Data 5X Columnar Archive Compression 7 Copyright 23, 22, Oracle and/or its affiliates. All rights reserved. Confidential Oracle Restricted

7 Oracle Advanced Compression Transparent, Smaller, Faster % Application Transparent End-to-end Cost/Performance Benefits across CPU, DRAM, Flash, Disk & Network Runs Faster: OLTP Apps (Transactional & Analytics) & DW Reduces Database Footprint CapEx & OpEx savings Increases Cloud ROI through Database Footprint reduction in DRAM Memory 8 Copyright 23, Oracle and/or its affiliates. All rights reserved.

8 Understanding Data Usage Patterns Database heat map Copyright 23, Oracle and/or its affiliates. All rights reserved.

9 Understanding Data Usage Patterns Database heat map Copyright 23, Oracle and/or its affiliates. All rights reserved.

10 Heat Map What it tracks Active Frequent Access Occasional Access Dormant HOT Actively updated Infrequently updated, Frequently queried Infrequent access for query and updates Long term analytics & compliance COLD Heat Map tracking Database level Heat Map shows which tables and partitions are being used Block level Heat Map shows last modification at the block level Comprehensive Segment level shows both reads and writes Distinguishes index lookups from full table scans Automatically excludes stats gathering, DDLs, table redefinitions, etc High Performance Object level at no cost Block level < 5% cost 2 Copyright 23, Oracle and/or its affiliates. All rights reserved.

11 Heat Map Enterprise Manager 3 Copyright 23, Oracle and/or its affiliates. All rights reserved.

12 Automatic Data Optimization Usage Based Data Compression Hot Data Warm Data Archive Data 3X Advanced Row Compression X Columnar Query Compression 5X Columnar Archive Compression 4 Copyright 23, 22, Oracle and/or its affiliates. All rights reserved. Confidential Oracle Restricted

13 Simple Declarative SQL extension Automatic Data Optimization ALTER TABLE sales ILM add Active Frequent Access Occasional Access Dormant OLTP Compressed (2-4x) Affects ONLY Candidate Rows Cached in DRAM & FLASH Warehouse Compressed (x) High Performance Storage Warehouse Compressed (x) Low Cost Storage Archive Compressed (5-5X) Archival Storage row store compress advanced row after 2 days of no update compress for query low after week of no update tier to SATA Tablespace compress for archive high after 6 months no access 5 Copyright 23, Oracle and/or its affiliates. All rights reserved.

14 Automatic Data Optimization Add compression and tiering policies to tables Policy Policy 2 Compress Partitions with columnar compression if they haven t been modified in 8 days Compress Partitions with row compression if they haven t been modified in 3 days Oldest Data Most Recent Data 6 Copyright 23, 22, Oracle and/or its affiliates. All rights reserved.

15 Automatic Data Optimization A heat map tracks the activity of segments and blocks Policy Policy 2 Oldest Data Most Recent Data 7 Copyright 23, 22, Oracle and/or its affiliates. All rights reserved.

16 Automatic Data Optimization Policies are automatically applied to tables Policy Policy 2 Oldest Data Most Recent Data 8 Copyright 23, 22, Oracle and/or its affiliates. All rights reserved.

17 Automatic Data Optimization Policies are automatically applied to tables Policy Policy 2 Oldest Data Most Recent Data 9 Copyright 23, 22, Oracle and/or its affiliates. All rights reserved.

18 Automatic Data Optimization Policies are automatically applied to tables Policy Policy 2 Oldest Data Most Recent Data 2 Copyright 23, 22, Oracle and/or its affiliates. All rights reserved.

19 Automatic Data Optimization Reduce storage footprint, read compressed data faster Policy Policy 2 Oldest Data Most Recent Data 2 Copyright 23, 22, Oracle and/or its affiliates. All rights reserved. Confidential Oracle Restricted

20 Automatic Data Optimization Automatically tier data to lower cost storage Policy Policy 2 Policy 2 Policy 3 Oldest Data If the tablespace is nearly full compress the oldest partition with archive compression and move it to Tier 2 Storage Most Recent Data 22 Copyright 23, 22, Oracle and/or its affiliates. All rights reserved.

21 Automatic Data Optimization OLTP Reporting Compliance & Reporting x compressed 5x compressed This Quarter This Year Prior Years Row Store for fast OLTP Compressed Column Store for fast analytics Archive Compressed Column Store for max compression As data cools down, Advanced Data Optimization automatically converts data to columnar compressed Online 23 Copyright 23, Oracle and/or its affiliates. All rights reserved.

22 Powerful Policy Specification Automatic Data Optimization Declarative Policy Specification: Condition Action alter table sales ilm add policy row store compress advanced segment after 3 days of no modification; Conditions are time period after creation, access, modification of data Actions can be Compression Tiering or Tablespace Tiering Policies are inherited from the tablespace or table New tables inherit from tablespace; can also be applied to existing tables New partitions (including interval partitions) inherit from table 24 Copyright 23, Oracle and/or its affiliates. All rights reserved.

23 Up to 5x Smaller Footprint & Faster Queries Automatic Data Optimization for OLTP Both Columnar & Archive Compression now complement Advanced Row Compression Best Practice: Step : Use Advanced Row Compression for entire DB and then Step 2: ADO automatically converts into columnar compressed once the updates cool down, and is used mainly for reporting => Query speed of Columnar & x smaller footprint Step 3: ADO automatically converts into archive compressed once data cools down further and is no longer frequently queried => 5-5x smaller footprint 25 Copyright 23, Oracle and/or its affiliates. All rights reserved.

24 Optimizes Data Based on Heat Map Automatic Data Optimization for DW Data generally comes in via Bulk Loading Workload dominated by queries, even during loading Step : Bulk Load directly into Columnar Compressed x smaller footprint, Query speed of Columnar Step 2: ADO automatically converts to Archive Compressed and moves to Lower Cost Storage once its queried infrequently Data remains online, with 5-5x smaller footprint, & lower storage cost 26 Copyright 23, Oracle and/or its affiliates. All rights reserved.

25 Fast, Flexible Loads & Queries on Columnar Automatic Data Optimization Mixed Use Fastest Load with uncompressed & Fastest Queries with columnar Mixed workloads often use Java app or 3rd party tools to insert and update data that does not use Bulk Loads, so cannot use Columnar Step : Load into uncompressed, conventional inserts & updates Fast loading, & flexibility of using a regular OLTP app for loading Step 2: ADO moves to Row Compressed or Columnar Compressed or Low Cost Storage once updates cool down Faster Queries, 3-x smaller footprint 27 Copyright 23, Oracle and/or its affiliates. All rights reserved.

26 Scheduled Policy Execution Automatic Data Optimization Immediate and background policy execution Policies are executed in maintenance windows Can be manually executed as needed Policies can be extended to incorporate Business Rules Users can add custom conditions to control placement (e.g. 3 months after the ship date of an order) 28 Copyright 23, Oracle and/or its affiliates. All rights reserved.

27 Optimized Backups Automated READONLY Data Movement SQL> ALTER TABLE EMPLOYEE ILM ADD POLICY TIER TO DATA2 READ ONLY AFTER 8 DAYS OF NO MODIFICATION 29 Copyright 23, Oracle and/or its affiliates. All rights reserved.

28 Backup & Recovery Automatic Data Optimization OLTP Reporting Compliance & Reporting Read / Write Tablespace x compressed Read-mostly data is moved to a READONLY Tablespace 5x compressed READONLY TBS As data cools down, Automatic Data Optimization automatically moves it to a READONLY TBS, it s backed up only once after that 3 Copyright 23, Oracle and/or its affiliates. All rights reserved.

29 Summary Heat Map & Automatic Data Optimization Heat Map Automatically tracks access Database-aware: maintenance jobs, backups, etc. don t affect Heat Map Automatic Data Optimization Declarative easy-to-use syntax to define data compression & movement policies Extensible with business-specific logic Automates and simplifies ILM for Oracle Database data 3 Copyright 23, Oracle and/or its affiliates. All rights reserved.

30 32 Copyright 23, Oracle and/or its affiliates. All rights reserved.