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Oracle 12c Analytics New Features
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Oracle 12c Analytics New Features


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  • 1. Oracle 12c Analytics New Features Husnu Sensoy Global Maksimum Data & Information Technologies
  • 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. New Features for Analytics • Partitioning • CBO • Advanced Analytics • Data Management
  • 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. 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. 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. 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. 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. 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. 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. Automatic Data Optimisation (ADO)
  • 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. Q& A