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AIOUG Techday August 23rd Hyderabad - 12c Theme
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12c In Memory Management - Saurabh Gupta
1.
2.
Oracle Database 12c
In-Memory Saurabh K. Gupta Database Product Management
3.
Who am I?
• Principal Technologist, Database Product Management • Author of “Oracle Advanced PL/SQL Developer Professional Guide”, Technical Reviewer, blogger • Experience in Oracle Databases, design, development and administration, High Availability solutions, Exadata Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 3
4.
Oracle Database In-Memory
Goals Real Time Accelerate OLTP Analytics No Changes to Applications Exploit latest generation hardware Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | CPU 100x 2x
5.
Become a Real-Time
Enterprise • Data-Driven • Rapidly make decisions based on real-time data • Agile AGILE DATA-DRIVEN • Respond quickly to change • Efficient • Continually improve processes and profitability Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 5 EFFICIENT
6.
Row Format Databases
vs. Column Format Databases Row Transactions run faster on row format – Example: Insert or query a sales order – Fast processing few rows, many columns SALES Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Column Analytics run faster on column format – Example : Report on sales totals by region – Fast accessing few columns, many rows SALES 6
7.
Row Format Databases
vs. Column Format Databases Row Insert a new sales order on row format – One row insert = FAST SALES INSERT Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 7 Column Insert a new sales order in Column Format – Many column inserts = S L O W SSAtoLErSes INSERT INSERT INSERT INSERT Until Now Must Choose One Format and Suffer Tradeoffs
8.
Breakthrough: Dual Format
Database • BOTH row and column formats for same table • Simultaneously active and transactionally consistent Memory Memory SALES SALES • Analytics reporting use new in-memory Column format • OLTP uses proven row format Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 8 Row Format Column Format
9.
OLTP is Slowed
Down by Analytic Indexes Insert rate decreases as number of indexes increases Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
10.
Column Store Replaces
Analytic Indexes • Fast analytics on any columns • Better for unpredictable analytics • Less tuning administration Table 1 – 3 OLTP Indexes In-Memory Column Store • Column Store not persistent so update cost is much lower • OLTP batch run faster Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 10
11.
Oracle In-Memory Requires
Zero Application Changes Full Functionality - No restrictions on SQL Easy to Implement - No migration of data Fully Compatible - All existing applications run unchanged Fully Multitenant - Oracle In-Memory is Cloud Ready Uniquely Achieves All In-Memory Benefits With No Application Changes Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 11
12.
Program Agenda
Configuring the In-Memory Column Store Populating the In-Memory Column Store Querying the In-Memory Column Store Monitoring the In-Memory Column Store Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 12
13.
Configuring : In-Memory
Column Store System Global Area SGA Buffer Cache Shared Pool Redo Buffer Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Large Pool Other shared Memory Components In-Memory Area
14.
Configuring : In-Memory
Column Store • Controlled by INMEMORY_SIZE parameter •Minimum size of 100MB • SGA_TARGET must be large SELECT * FROM V$SGA; NAME VALUE ------------------ --------- enough to accommodate • Static Pool Fixed Size 2927176 Variable Size 570426808 Database Buffers 4634022912 Redo Buffers 13848576 In-Memory Area 1024483648 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
15.
Program Agenda
Configuring the In-Memory Column Store Populating the In-Memory Column Store Querying the In-Memory Column Store Monitoring the In-Memory Column Store Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 15
16.
Oracle In-Memory Columnar
Technology • Pure in-memory column format • Not persistent, and no logging • Quick to change data: fast OLTP • 2x to 20x compression Pure In-Memory Columnar • Enabled at table or partition level • Available on all hardware platforms Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 16 SALES
17.
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 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 17
18.
Populating : In-Memory
Column Store • New INMEMORY ATTRIBUTE • Following segment types are eligible • Tables • Partitions ALTER TABLE sales INMEMORY; ALTER TABLE sales NO INMEMORY; • Subpartition • Materialized views • Following segment types not eligible • IOTs • Hash clusters • Out of line LOBs Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | CREATE TABLE customers …… PARTITION BY LIST (PARTITION p1 …… INMEMORY, (PARTITION p2 …… NO INMEMORY); Pure OLTP Features
19.
Populating : In-Memory
Column Store • Possible to populate only certain columns from a table or partition • Order in which objects are populated controlled by ALTER TABLE sales INMEMORY NO INMEMORY (PROD_ID); PRIORITY subclause • Critical, high, medium, low • Default – none (populate on first access) • Does not control the speed of population Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | CREATE TABLE orders (c1 number, c2 varchar(20), c3 number) INMEMORY PRIORITY CRITICAL NO INMEMORY (c1);
20.
Populating : In-Memory
Column Store • Objects compressed during population • New compression techniques • Focused on scan performance ALTER MATERIALIZED VIEW mv1 INMEMORY MEMCOMPRESS FOR QUERY; • Controlled by MEMCOMPRESS subclause • Multiple levels of compression • Possible to use a different level for different partitions in a table Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | CREATE TABLE trades (Name varchar(20), Desc varchar(200)) INMEMORY MEMCOMPRESS FOR DML(desc);
21.
Populating : In-Memory
Column Store • Different levels • FOR DML Use on tables or partitions with very active DML activity • FOR QUERY CREATE TABLE ORDERS …… PARTITION BY RANGE …… (PARTITION p1 …… INMEMORY NO MEMCOMPRESS PARTITION p2 …… INMEMORY MEMCOMPRESS FOR DML, Default mode for most tables • FOR CAPACITY For less frequently accessed segments • Easy to switch levels as part of ILM strategy Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | PARTITION p3 …… INMEMORY MEMCOMPRESS FOR QUERY, : PARTITION p200 …… INMEMORY MEMCOMPRESS FOR CAPACITY );
22.
Identifying : Tables
With INMEMORY Attribute • New INMEMORY column in *_TABLES dictionary tables • INMEMORY is a segment attribute SELECT table_name, inmemory FROM USER_TABLES; TABLE_NAME INMEMORY • USER_TABLESdoesn’t display Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | ------------ -------- CHANNELS DISABLED COSTS CUSTOMERS DISABLED PRODUCTS ENABLED SALES TIMES DISABLED segment attributes for logical objects • Both COSTS SALES are partitioned = logical objects • INMEMORY attribute also reported in *_TAB_PARTITIONS
23.
Identifying : Tables
With INMEMORY Attribute • New view v$IM_SEGMENTS • Indicate: • Objects populated in memory • Current population status SELECT segment_name name, population_status status FROM v$IM_SEGMENTS; • Can also be used to determine compression ratio achieved Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | NAME STATUS ------------ -------- PRODUCTS COMPLETED SALES STARTED
24.
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 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
25.
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 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
26.
Program Agenda
Configuring the In-Memory Column Store Populating the In-Memory Column Store Querying the In-Memory Column Store Monitoring the In-Memory Column Store Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 26
27.
Why is an
In-Memory scan faster than the buffer cache? SELECT COL4 FROM MYTABLE; X X Buffer Cache Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 27 X X X RESULT Row Format
28.
Why is an
In-Memory scan faster than the buffer cache? SELECT COL4 FROM MYTABLE; IM Column Store RESULT Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 28 Column Format RESULT X X X X
29.
Oracle In-Memory Column
Store Storage Index • Each column is the made up of multiple column units • Min / max value is recorded for each column unit in a storage index Example: Find sales from stores with a store_id of 8 or higher Memory Min 1 Max 3 Min 4 • Storage index provides partition pruning like performance for ALL queries Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 29 SALES Column Format Max 7 Min 8 Max 12 Min 13 Max 15
30.
Orders of Magnitude
Faster Analytic Data Scans CPU PROMO_ID Example: Find all sales With PROMO_ID 9999 Memory • Each CPU core scans local in-memory columns • Scans use super fast SIMD vector instructions Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 30 Load multiple PROMO_ID values Vector Compare all values an 1 cycle 9999 9999 9999 9999 VECTOR REGISTER • Originally designed for graphics science • Billions of rows/sec scan rate per CPU core • Row format is millions/sec
31.
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 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
32.
Identifying : INMEMORY
Table Scan • NEWSession level statistics • Best way to determine if In-Memory was use • Best way to measure the benefits of In-Memory scan Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
33.
Joining and Combining
Data Also Dramatically Faster • Converts joins of data in multiple tables into fast column scans Example:Find all orders placed on Christmas eve DATE_DIM LINEORDER Datekey is 24122013 Date DateKey • Joins tables 10x faster Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 33 DateKey Type=d.d_date='December 24, 2013' Amount Sum
34.
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 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
35.
Multiple bloom filter
• Multi-table joins are common in analytic queries • Possible to apply multiple bloom filters to the fact table due to sophisticated Select d.d_year, s.s_nation, sum(lo_revenue - lo_supplycost) From LINEORDER l, DATE_DIM d, PART p, SUPPLIER s Where l.lo_orderdate = d.d_datekey And l.lo_partkey = p.p_partkey Optimizer • Simultaneously joining to all of the dimension tables while scanning the fact table Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | And l.lo_suppkey = s.s_suppkey And p.p_mfgr= 'MFGR#12’ And s.s_region = 'AMERICA’ Group by d.d_year, s.s_nation Order by d.d_year, s.s_nation;
36.
Multiple Bloom Filter
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
37.
In-Memory Aggregation •
Dynamically creates in-memory report outline • Then report outline filled-in during fast fact scan Example: Report sales of footwear in outlet stores Sales Products In-Memory Report Outline Footwear $ • Reports run much faster without predefined cubes Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 37 Stores Outlets Footwear Outlets Sales $$ $ $$$
38.
Identifying : INMEMORY
Aggregation Hash Group By MMoonniittoorriinngg Monitoring tthhee the IInn--In-MMeemmoorryy CCoolluummnn SSttoorree Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Vector Group By
39.
Program Agenda
Configuring the In-Memory Column Store Populating the In-Memory Column Store Querying the In-Memory Column Store Monitoring the In-Memory Column Store Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 39
40.
New In-Memory Central
Screen in EM In-Memory Area (GB) :4.00 In-Memory Area Used (GB) :1.79 Object map integrated with 12c heatmap feature New In-Memory Central Screen in EM Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
41.
New In-Memory Central
Screen in EM Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
42.
New In-Memory Central
Screen in EM Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
43.
New In-Memory Entries
in CPU Wait Class Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
44.
New In-Memory Entries
in CPU Wait Class Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
45.
In-Memory Query in
SQL Monitor Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
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