Well-Balanced Successive Simple-9 for Inverted Lists Compression

The growth in the amount of information available on the Internet and thousands of user queries per second brings huge challenges to the index update and query processing of search engines. Index compression is partially responsible for the current performance achievements of existing search engines. The selection of the index compression algorithms must weigh three factors, i.e., compression ratio, compression speed and decompression speed. In this paper, we study the well-known Simple9 compression, in which exist many branch operations, table lookup and data transfer operations when processing each 32-bit machine word. To enhance the compression and decompression performance of Simple-9 algorithm, we propose a successive storage structure and processing metric to compress two successive Simple-9 encoded sequence of integers in a single data processing procedure, thus the name Successive Simple-9 (SSimple9). In essence, the algorithm shortens the process of branch operations, table lookup and data transfer operations when compressing the integer sequence. More precisely, we initially present the data storage format and mask table of SSimple-9 algorithm. Then, for each mode in the mask table, we design and hard-code the main steps of the compression and decompression processes. Finally, analysis and comparison on the experimental results of the simulation and TREC datasets show the compression and decompression efficiency speedup of the proposed SSimple-9 algorithm. key words: Successive Simple-9, successive storage, inverted index, decompression performance