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 busi...
New Features for Analytics
•

Partitioning

•

CBO

•

Advanced Analytics

•

Data Management
Partitioning
•

Core Functionality
•

•

Interval-REF Partitioning

Performance
•

•
•

Partition Maintenance on multiple
...
Cost Based Optimiser
•

Adaptive Statistics
•

Dynamic Sampling (LEVEL=11)

•

Cardinality Feedback Enhancement
•

Re-opti...
Adaptive Query Optimisation
SELECT product_name
FROM
order_items o,
product_information p
WHERE o.unit_price = 15
AND o.qu...
Adaptive Query Optimisation
•

Join method decision deferred until runtime
•
•

Alternate sub-plans are pre-computed and s...
Advanced Analytics
•

Oracle Advanced Analytics 12c
•

New Data Mining Algorithms
•
•

SVD - PCA

•
•

EM (Expectation Max...
Predictive Queries
SELECT cust_income_level,
cust_id,
Round(prob_anom, 2)
prob_anom,
Round(pctrank, 3) * 100 pct_rank
FROM...
SQL Pattern Matching
X YWZ
first_x
1

9

9

13
1

last_z
19

13
19
SELECT first_x, last_z
FROM ticker MATCH_RECOGNIZE (
PAR...
Automatic Data Optimisation
(ADO)
Automatic Data Optimisation (ADO)
Policy

Active/Hot

Frequently Accessed
Occasional Access
Dormant

ALTER TABLE sales ILM...
Q& A
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Oracle 12c Analytics New Features

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Oracle 12c Analytics New Features

  1. 1. Oracle 12c Analytics New Features Husnu Sensoy Global Maksimum Data & Information Technologies
  2. 2. 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
  3. 3. New Features for Analytics • Partitioning • CBO • Advanced Analytics • Data Management
  4. 4. 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
  5. 5. Cost Based Optimiser • Adaptive Statistics • Dynamic Sampling (LEVEL=11) • Cardinality Feedback Enhancement • Re-optimisation • Histograms • Better and Faster Statistics Gathering • • Session private statistics on GTT • • STATS_ON_LOAD: For CTAS and IAS on empty tables Concurrent statistics gathering Adaptive Plans • Join methods • Parallel distribution methods
  6. 6. Adaptive Query Optimisation SELECT 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 threshold Stats collector Table scan order_items Index scan prod_info_idx Table scan product_information
  7. 7. Adaptive Query Optimisation • Join method decision deferred until runtime • • Alternate sub-plans are pre-computed and stored in the cursor • • Default plan is computed using available statistics Statistic collectors are inserted at key points in the plan Data distribution method can also be changed during execution.
  8. 8. Advanced Analytics • Oracle Advanced Analytics 12c • New Data Mining Algorithms • • SVD - PCA • • EM (Expectation Maximisation) Predictive Queries Oracle Data Miner/SQL Developer 4.0 • • SQL Query Node • • New Graph Node (box,scatter, bar,histogram) R Script Node Oracle Advanced Analytics/ORE 1.3 • Neural Networks • Improved integration with OBIEE
  9. 9. Predictive Queries SELECT 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
  10. 10. SQL Pattern Matching X YWZ first_x 1 9 9 13 1 last_z 19 13 19 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))
  11. 11. Automatic Data Optimisation (ADO)
  12. 12. Automatic Data Optimisation (ADO) Policy Active/Hot Frequently Accessed Occasional Access Dormant ALTER TABLE sales ILM ADD row store compress advanced row after 2 DAYS OF NO_MODIFICATION; ALTER TABLE sales ILM ADD compress for query low after 7 DAYS OF NO_MODIFICATION; ALTER TABLE sales ILM ADD TIER TO sata_tbs AFTER 1 MONTH OF NO ACCESS; ALTER TABLE sales ILM ADD compress for archive high AFTER 7 MONTHS OF NO ACCESS;
  13. 13. Q& A
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