An agile big data analytic engine

The BigObject: What and Why? to analyze big data on real-time basis Mission an agile analytic engine which stores and computes big data on commodity machines. Position

The BigObject: Target 10 6 Computations/sec Mega Operations 10 9 Computation/sec Giga Operations 10 6 – 10 9 per sec ► Exploit the power of hardware ► Maximize the performance a single machine can achieve Our Focus

Application Computing Engine for BI Tool –Multi-dimensional Infographics –Pre-built Components: Association for Recommendation System Significance for Market Segmentation Log Analysis –Exception Detection Computing Engine in Scientific Fields –Climate Simulation –DNA Sequencing

Performance Compute 1M Data Records Compute 100M Data Records 0.07 BigObject MySQL PostgresSQL Commercial DB

Why the BigObject Outperforms Others? Technical Principles of the BigObject

Dealing With Big Data The Portraits of Big Data –3Vs of big data: Volume, Velocity, Variety –We have dealt with Volume by Scale-out and Velocity by Scale-up Another V shouldn’t be neglected – Valence, the degree of interdependency among data components, which normally causes data shuffling. In-place Computing Model is designed to solve high-valence big data problems.

Scale-Out, Scale-Up, and Spread out the data components over a flat, virtually infinite address space, where data are ready for the CPU to compute. Scale-In Scale-Out Scale-Up

2 64 : Nearly Infinite The introduction of 64-bit CPU evokes revisit to the software discipline. When address space is nearly infinite, why don’t we place the data components over it and make them ready for computations instead of moving the data to program?

Time to Revisit the Computing Model Traditional Approach In-place Approach CPU File Virtual Memory Space In-place Object CPU DISK Database Table RAM 1. Data Retrievals 2. Juggling 3. Swapping Paging (On-demand)

The BigObject Data live and work in a flat and infinite address space. Big data is organized in the way able to trade time with space. In-place Computing ApproachAn in-memory database (no ACID) Can be implemented on every data node. Complementary to Distributed Approach

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