Oracle 12c Analytics New Features

Husnu Sensoy Global Maksimum Data & Information Technologies

Global Maksimum Data & Information Technologies

• Complex Event Processing

• Oracle CEP

• Making hundred of different business decisions for millions of events in a second

• Advanced Analytics

• Oracle Data Mining

• Oracle R Enterprise

• Large scale data analytics

• Ten billion rows in a week

• Data Visualisation

• State of the art data visualisation

• DIY BI

New Features for Analytics

• Partitioning

• CBO

• Advanced Analytics

• Data Management

Partitioning• Core Functionality

• Interval-REF Partitioning

• Performance

• Partition Maintenance on multiple partitions

• Partial local and global indexes

• Manageability

• Asynchronous global index maintenance for DROP/TRUNCATE

• Online partition MOVE

• Cascading TRUNCATE/EXCHANGE

Cost Based Optimiser• Adaptive Statistics

• Dynamic Sampling (LEVEL=11)

• Cardinality Feedback Enhancement

• Re-optimisation

• Histograms

• Better and Faster Statistics Gathering

• STATS_ON_LOAD: For CTAS and IAS on empty tables

• Session private statistics on GTT

• Concurrent statistics gathering

• Adaptive Plans

• Join methods

• Parallel distribution methods

Adaptive Query OptimisationSELECT product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND o.quantity > 1 AND p.product_id = o.product_id

NESTED LOOP HASH JOIN

Table scan order_items

Index scan prod_info_idx

Table scan product_information

Stats collector

threshold

Adaptive Query Optimisation• Join method decision deferred until runtime

• Default plan is computed using available statistics

• Alternate sub-plans are pre-computed and stored in the cursor

• Statistic collectors are inserted at key points in the plan

• Data distribution method can also be changed during execution.

Advanced Analytics• Oracle Advanced Analytics 12c

• New Data Mining Algorithms

• EM (Expectation Maximisation)

• SVD - PCA

• Predictive Queries

• Oracle Data Miner/SQL Developer 4.0

• New Graph Node (box,scatter, bar,histogram)

• SQL Query Node

• R Script Node

• Oracle Advanced Analytics/ORE 1.3

• Neural Networks

• Improved integration with OBIEE

Predictive QueriesSELECT cust_income_level, cust_id, Round(prob_anom, 2) prob_anom, Round(pctrank, 3) * 100 pct_rank FROM (SELECT cust_id, cust_income_level, prob_anom, Percent_rank() over( PARTITION BY cust_income_level ORDER BY prob_anom DESC) AS pct_rank FROM (SELECT cust_id, cust_income_level, Prediction_probability(OF ANOMALY,0 using *) over( PARTITION BY cust_income_level) prob_anom FROM customers)) WHERE pct_rank <= .05 ORDER BY cust_income_level, prob_anom desc

SQL Pattern MatchingX Y W Z

SELECT first_x, last_z FROM ticker MATCH_RECOGNIZE ( PARTITION BY name ORDER BY time MEASURES FIRST(x.time) AS first_x LAST(z.time) AS last_z ONE ROW PER MATCH PATTERN (X+ Y+ W+ Z+) DEFINE X AS (price < PREV(price)) Y AS (price > PREV(price)) W AS (price < PREV(price)) Z AS (price > PREV(price))

first_x last_z1 9

13 19

1 9 13 19

Automatic Data Optimisation (ADO)

Automatic Data Optimisation (ADO)

Policy

Active/HotALTER TABLE sales ILM ADD row store compress advanced row after 2 DAYS OF NO_MODIFICATION;

Frequently AccessedALTER TABLE sales ILM ADD compress for query low after 7 DAYS OF NO_MODIFICATION;

Occasional Access ALTER TABLE sales ILM ADD TIER TO sata_tbs AFTER 1 MONTH OF NO ACCESS;

DormantALTER TABLE sales ILM ADD compress for archive high AFTER 7 MONTHS OF NO ACCESS;

Q& A