IISWC 2007 Panel Analyzing Petabytes Suchi Raman Netezza Corp.

2 Netezza Confidential Petabyte Database Workloads Macro-analytic queries > Identify trends and patterns > Very large data volumes > Query times dominated by disk scan times Micro-analytic queries > Short running queries > Query run once and stored > Pre-computed summaries Data management > ETL load/unload > Backup/restore

3 Netezza Confidential Netezza NPS System

4 Netezza Confidential Software challenges Effective disk bandwidth > Optimal data layouts > Data compression > Increased effective disk bandwidth (and reliability!) > Upgrades and evolution of on-disk formats > Minimize disk reads (indexes, caches) Query processing algorithms > Skew avoidance algorithms > Scheduling among queries, especially with mixed workloads combining large and small queries System Monitoring/profiling > System monitoring during busy periods > Accurate profiling techniques Data management challenges > High speed data path in/out of NPS system > Efficient/flexible data formats for load/unload > Infrastructure challenge – fast external devices for sourcing/sinking data > Custom functions (UDFs/UDAs) implemented within the system

5 Netezza Confidential Hardware challenges > Increased effective disk bandwidth (and reliability!) > Multi-core technology > Balancing CPU-to-disk ratio > Specialized engines (e.g., FPGA-based filtering) > Faster internal and external connectivity

6 Netezza Confidential How can University Researchers contribute? Explore new applications and data types > E.g., network traffic analysis > Geospatial data > Biological data types > Skew avoidance/scheduling algorithms > Applications built on UDFs/UDAs > Verification methods for optimizer algorithms Platform improvements > Disk performance and reliability > FPGA filtering algorithms > Faster interconnect networks > Power and cooling improvements