NDLI: Constant-Time Query Processing

Content Provider	IEEE Xplore Digital Library
Author	Raman, V. Swart, G. Lin Qiao Reiss, F. Dialani, V. Kossmann, D. Narang, I. Sidle, R.
Copyright Year	2008
Description	Author affiliation: Almaden Res. Center, IBM, San Jose, CA (Raman, V.)
Abstract	Query performance in current systems depends significantly on tuning: how well the query matches the available indexes, materialized views etc. Even in a well tuned system, there are always some queries that take much longer than others. This frustrates users who increasingly want consistent response times to ad hoc queries. We argue that query processors should instead aim for constant response times for all queries, with no assumption about tuning. We present Blink, our first attempt at this goal, that runs every query as a table scan over a fully denormalized database, with hash group-by done along the way. To make this scan efficient, Blink uses a novel compression scheme that horizontally partitions tuples by frequency, thereby compressing skewed data almost down to entropy, even while producing long runs of fixed-length, easily-parseable values. We also present a scheme for evaluating a conjunction of range and equality predicates in SIMD fashion over compressed tuples, and different schemes for efficient hash-based aggregation within the L2 cache. A experimental study with a suite of arbitrary single block SQL queries over a TPCH-like schema suggests that constant-time queries can be efficient.
Starting Page	60
Ending Page	69
File Size	5653530
Page Count	10
File Format	PDF
ISBN	9781424418367
DOI	10.1109/ICDE.2008.4497414
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-04-07
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Query processing Costs Delay Frequency Entropy Databases Hardware Data structures Tuning Humans
Content Type	Text
Resource Type	Article

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