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Altibase DSM: CTable for Pull-based
                                Processing in SPE
                                Jaemyung Kim, Vladimir Verjovkin, Sergey A. Fedorov, Younghun Kim,
                                Dae-Il Kim, Sungjin Kim, Sang-Won Lee @ Altibase Corp. & SKKU
Data Processing Paradigm




                           Pull-based Processing                                  Push-based Processing
                                                                                         2. Data (Event)
                                CPU Usage for last 30 seconds:                           Occurrence
                                                                                                                                 3. Push Output

                                SELECT AVG(CPU_RATE)                                                          CEP Engine
                                  FROM CPUStatus                                                            (Complex Event
                                                                                                              Processing)
                                 WHERE Time > sysdate – INTERVAL ‘30’ SECOND;
                                                                                                           1. Register a query

                                  1. Data
                                  Occurrence
                                                                3. Query                 CPU Usage for last 30 seconds:

                                                        DBMS                             SELECT AVG(CPU_RATE)
                                2. Insert Data
                                                               4. Fetch Records            FROM CPUStatus KEEP INTERVAL ‘30’ SECOND;
                                Into Relational Table
                                                               (Output)




                            Altibase DSM CTable
CTable Feature




                            • Pull-based processing (JDBC, ODBC, Python DB API )

                            • Distributed key-value store

                            • Seamless integration with streams and windows

                            • Update propagation using streams through shared
                            memory, unicast, and multicast




                            Sex-Offender Tracking System                          Bus Arrival Information System
Use Cases




                           Q1. Sex-offender movement tracking                      Q2. Upcoming buses in the bus stop
Example Queries




                           (Continuous Query, Push-based)                          (CTable Query, Pull-based)
                           SELECT 'VIOLATION DETECTED', *                          SELECT bus.bus_no, bus.license_plate,
                             FROM ctable(resident_limitation) rl,                         r.ord_id-cb.ord_id||' stops away' distance
                                  location_info l                                    FROM ctable(bus_route) r, ctable(bus_route) cb,
                            WHERE rl.unit_id = l.unit_id                                  ctable(bus_location) bus
                              AND sqrt( (l.x-rl.x)*(l.x-rl.x)                       WHERE r.stn_id = ? /* specific bus stop id */
                                        + (l.y-rl.y)*(l.y-rl.y) )                     AND r.ord_id >= cb.ord_id
                                  < rl.radius;                                        AND cb.stn_id = bus.stn_id
                                                                                    ORDER BY r.ord_id-cb.ord_id, bus.bus_no ASC;


                                                    DEBS’11, July 11–15, 2011, New York, New York, USA.

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Altibase DSM: CTable for Pull-based Processing in SPE

  • 1. Altibase DSM: CTable for Pull-based Processing in SPE Jaemyung Kim, Vladimir Verjovkin, Sergey A. Fedorov, Younghun Kim, Dae-Il Kim, Sungjin Kim, Sang-Won Lee @ Altibase Corp. & SKKU Data Processing Paradigm Pull-based Processing Push-based Processing 2. Data (Event) CPU Usage for last 30 seconds: Occurrence 3. Push Output SELECT AVG(CPU_RATE) CEP Engine FROM CPUStatus (Complex Event Processing) WHERE Time > sysdate – INTERVAL ‘30’ SECOND; 1. Register a query 1. Data Occurrence 3. Query CPU Usage for last 30 seconds: DBMS SELECT AVG(CPU_RATE) 2. Insert Data 4. Fetch Records FROM CPUStatus KEEP INTERVAL ‘30’ SECOND; Into Relational Table (Output) Altibase DSM CTable CTable Feature • Pull-based processing (JDBC, ODBC, Python DB API ) • Distributed key-value store • Seamless integration with streams and windows • Update propagation using streams through shared memory, unicast, and multicast Sex-Offender Tracking System Bus Arrival Information System Use Cases Q1. Sex-offender movement tracking Q2. Upcoming buses in the bus stop Example Queries (Continuous Query, Push-based) (CTable Query, Pull-based) SELECT 'VIOLATION DETECTED', * SELECT bus.bus_no, bus.license_plate, FROM ctable(resident_limitation) rl, r.ord_id-cb.ord_id||' stops away' distance location_info l FROM ctable(bus_route) r, ctable(bus_route) cb, WHERE rl.unit_id = l.unit_id ctable(bus_location) bus AND sqrt( (l.x-rl.x)*(l.x-rl.x) WHERE r.stn_id = ? /* specific bus stop id */ + (l.y-rl.y)*(l.y-rl.y) ) AND r.ord_id >= cb.ord_id < rl.radius; AND cb.stn_id = bus.stn_id ORDER BY r.ord_id-cb.ord_id, bus.bus_no ASC; DEBS’11, July 11–15, 2011, New York, New York, USA.