Safe Harbor Statement

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2 Safe Harbor Statement 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

3 Database In-Memory Ashish Gandotra Senior Solution Specialist

4 Oracle Database In-Memory Goals Real Time Analytics Accelerate Mixed Workload OLTP No Changes to Applications Trivial to Implement 100x 2x 4

5 Breakthrough: Dual Format Database Memory SALES Row Format Memory SALES Column Format BOTH row and column formats for same table Simultaneously active and transactionally consistent Analytics & reporting use new in-memory Column format OLTP uses proven row format 5

6 Why is an In-Memory scan faster than the buffer cache? Buffer Cache SELECT COL4 FROM MYTABLE; X X X X X RESULT Row Format 6

7 Why is an In-Memory scan faster than the buffer cache? IM Column Store SELECT COL4 FROM MYTABLE; Column Format X X X X RESULT 7

8 Program Agenda Configuring the In-Memory Column Store Populating the In-Memory Column Store Querying the In-Memory Column Store Managing the In-Memory Column Store on RAC Monitoring the In-Memory Column Store 8

9 Configuring : In-Memory Column Store System Global Area SGA Buffer Cache Shared Pool Redo Buffer Large Pool Other shared Memory Components In-Memory Area

10 Configuring : In-Memory Column Store SELECT * FROM V$SGA; NAME VALUE Fixed Size Variable Size Database Buffers Redo Buffers In-Memory Area Controlled by INMEMORY_SIZE parameter Minimum size of 100MB SGA_TARGET must be large enough to accommodate Static Pool

11 Program Agenda Configuring the In-Memory Column Store Populating the In-Memory Column Store Querying the In-Memory Column Store Managing the In-Memory Column Store on RAC Monitoring the In-Memory Column Store 11

12 Populating : In-Memory Column Store Populate is the term used to bring data into the In-Memory column store Populate is used instead of load because load is commonly used to mean inserting new data into the database Populate doesn t bring new data into the database, it brings existing data into memory and formats it in an optimized columnar format Population is completed by a new set of background processes ORA_W001_orcl Number of processes controlled by INMEMORY_MAX_POPULATE_SERVERS 13

13 Populating : In-Memory Column Store ALTER TABLE sales INMEMORY; ALTER TABLE sales NO INMEMORY; CREATE TABLE customers PARTITION BY LIST (PARTITION p1 INMEMORY, (PARTITION p2 NO INMEMORY); New INMEMORY ATTRIBUTE Following segment types are eligible Tables Partitions Subpartition Materialized views Following segment types not eligible IOTs Hash clusters Out of line LOBs Pure OLTP Features

14 Populating : In-Memory Column Store CREATE TABLE ORDERS PARTITION BY RANGE (PARTITION p1 INMEMORY NO MEMCOMPRESS PARTITION p2 INMEMORY MEMCOMPRESS FOR DML, PARTITION p3 INMEMORY MEMCOMPRESS FOR QUERY, : PARTITION p200 INMEMORY MEMCOMPRESS FOR CAPACITY ); Different levels FOR DML Use on tables or partitions with very active DML activity FOR QUERY Default mode for most tables FOR CAPACITY For less frequently accessed segments Easy to switch levels as part of ILM strategy

15 Identifying : Tables With INMEMORY Attribute SELECT table_name, inmemory FROM USER_TABLES; TABLE_NAME INMEMORY CHANNELS DISABLED COSTS CUSTOMERS DISABLED PRODUCTS ENABLED SALES TIMES DISABLED New INMEMORY column in *_TABLES dictionary tables INMEMORY is a segment attribute USER_TABLES doesn t display segment attributes for logical objects Both COSTS & SALES are partitioned => logical objects INMEMORY attribute also reported in *_TAB_PARTITIONS

16 Identifying : Tables With INMEMORY Attribute SELECT segment_name name, population_status status FROM v$im_segments; NAME STATUS PRODUCTS COMPLETED SALES STARTED New view v$im_segments Indicate: Objects populated in memory Current population status Can also be used to determine compression ratio achieved

17 Oracle Compression Advisor And In-Memory Easy way to determine memory requirements Use DBMS_COMPRESSION Applies MEMCOMPRESS to sample set of data from a table Returns estimated compression ratio

18 Oracle In-Memory Advisor New In-Memory Advisor Analyzes existing DB workload via AWR & ASH repositories Provides list of objects that would benefit most from being populated into IM column store

19 Program Agenda Configuring the In-Memory Column Store Populating the In-Memory Column Store Querying the In-Memory Column Store Managing the In-Memory Column Store on RAC Monitoring the In-Memory Column Store 24

20 Oracle In-Memory Column Store Storage Index Example: Find sales from stores with a store_id of 8 or higher Memory Min 1 Max 3 Min 4 Max 7 Each column is the made up of multiple column units Min / max value is recorded for each column unit in a storage index SALES Column Format Min 8 Max 12 Min 13 Max 15 Storage index provides partition pruning like performance for ALL queries 25

21 Identifying : INMEMORY Table Scan Optimizer fully aware Cost model adapted to consider INMEMORY scan New access method TABLE ACCESS IN MEMORY FULL Can be disabled via new parameter INMEMORY_QUERY

22 DateKey Amount Date DateKey Joining and Combining Data Also Dramatically Faster Example: Find all orders placed on Christmas eve DATE_DIM Datekey is LINEORDER Converts joins of data in multiple tables into fast column scans Joins tables 10x faster Type=d.d_date='December 24, 2013' Sum 29

23 Identifying : INMEMORY Joins Bloom filters enable joins to be converted into fast column scans Tried and true technology originally released in 10g Same technique used to offload joins on Exadata

24 Program Agenda Configuring the In-Memory Column Store Populating the In-Memory Column Store Querying the In-Memory Column Store Managing the In-Memory Column Store on RAC Monitoring the In-Memory Column Store 47

25 Scale-Out In-Memory Database to Any Size Scale-Out across servers to grow memory and CPUs In-Memory queries parallelized across servers to access local column data Scale-out policy is a segment level (table, partition, sub partition) property 48

26 Scale-Out In-Memory Database to Any Size ALTER TABLE sales INMEMORY DISTRIBUTE BY PARTITION; ALTER TABLE COSTS INMEMORY DISTRIBUTE AUTO; Policy is user-specifiable Controlled by DISTRIBUTE subclause Distribute by rowid range Distribute by partition Distribute AUTO 49

27 In-Memory Speed + Capacity of Low Cost Disk DRAM PCI FLASH DISK Hottest Data Active Data Cold Data Size not limited by memory Data transparently accessed across tiers Each tier has specialized algorithms & compression Speed of DRAM I/Os of Flash Cost of Disk

28 In-Memory & Partitioning For Seamless Scale Out Oracle smart enough to access data across tiers in the most efficient way 51

29 Oracle Database In-Memory: Unique Fault Tolerance Only Available on Engineered Systems Similar to storage mirroring Duplicate in-memory columns on another node Enabled per table/partition Application transparent Downtime eliminated by using duplicate after failure 52

30 Program Agenda Configuring the In-Memory Column Store Populating the In-Memory Column Store Querying the In-Memory Column Store Managing the In-Memory Column Store on RAC Monitoring the In-Memory Column Store 59

31 New In-Memory Central Screen in EM New In-Memory Central Screen in EM Object map integrated with 12c heatmap feature In-Memory Area (GB) :4.00 In-Memory Area Used (GB) :1.79

32 New In-Memory Central Screen in EM

33 New In-Memory Central Screen in EM

34 In-Memory Query in SQL Monitor

35 Summary: Oracle Database In-Memory Powering the Real-Time Enterprise DATA- DRIVEN AGILE Extreme Performance: Analytics & OLTP Extreme Scale-Out & Scale-Up Extreme Availability Extreme Simplicity EFFICIENT 73

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Who am I? Copyright 2014, Oracle and/or its affiliates. All rights reserved. 3

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