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- research-articleJuly 2021
Hyperspace: the indexing subsystem of azure synapse
- Rahul Potharaju,
- Terry Kim,
- Eunjin Song,
- Wentao Wu,
- Lev Novik,
- Apoorve Dave,
- Andrew Fogarty,
- Pouria Pirzadeh,
- Vidip Acharya,
- Gurleen Dhody,
- Jiying Li,
- Sinduja Ramanujam,
- Nicolas Bruno,
- César A. Galindo-Legaria,
- Vivek Narasayya,
- Surajit Chaudhuri,
- Anil K. Nori,
- Tomas Talius,
- Raghu Ramakrishnan
Proceedings of the VLDB Endowment (PVLDB), Volume 14, Issue 12Pages 3043–3055https://doi.org/10.14778/3476311.3476382Microsoft recently introduced Azure Synapse Analytics, which offers an integrated experience across data ingestion, storage, and querying in Apache Spark and T-SQL over data in the lake, including files and warehouse tables. In this paper, we present our ...
- articleFebruary 2010
Constrained physical design tuning
The VLDB Journal — The International Journal on Very Large Data Bases (VLDB), Volume 19, Issue 1Pages 21–44https://doi.org/10.1007/s00778-009-0154-1Existing solutions to the automated physical design problem in database systems attempt to minimize execution costs of input workloads for a given storage constraint. In this work, we argue that this model is not flexible enough to address several real-...
- demonstrationJune 2009
Interactive plan hints for query optimization
SIGMOD '09: Proceedings of the 2009 ACM SIGMOD International Conference on Management of dataJune 2009, Pages 1043–1046https://doi.org/10.1145/1559845.1559976Commercial database systems expose query hints to fix poor plans produced by the query optimizer. However, current query hints are not flexible enough to deal with a variety of non-trivial scenarios, and can be at times cumbersome for DBAs to interact ...
- ArticleMarch 2009
Power Hints for Query Optimization
ICDE '09: Proceedings of the 2009 IEEE International Conference on Data EngineeringMarch 2009, Pages 469–480https://doi.org/10.1109/ICDE.2009.68Commercial database systems expose query hints to address situations in which the optimizer chooses a poor plan for a given query. However, current query hints are not flexible enough to deal with a variety of non-trivial scenarios. In this paper, we ...
- research-articleAugust 2008
Constrained physical design tuning
Proceedings of the VLDB Endowment (PVLDB), Volume 1, Issue 1Pages 4–15https://doi.org/10.14778/1453856.1453863Existing solutions to the automated physical design problem in database systems attempt to minimize execution costs of input workloads for a given a storage constraint. In this paper, we argue that this model is not flexible enough to address several ...
- articleNovember 2007
Physical design refinement: The ‘merge-reduce’ approach
ACM Transactions on Database Systems (TODS), Volume 32, Issue 4Pages 28–eshttps://doi.org/10.1145/1292609.1292618Physical database design tools rely on a DBA-provided workload to pick an “optimal” set of indexes and materialized views. Such tools allow either creating a new such configuration or adding new structures to existing ones. However, these tools do not ...
- ArticleJune 2007
Online autoadmin: (physical design tuning)
SIGMOD '07: Proceedings of the 2007 ACM SIGMOD international conference on Management of dataJune 2007, Pages 1067–1069https://doi.org/10.1145/1247480.1247608Existing solutions for the automated physical design problem require explicit invocations of tuning tools and critically depend on DBAs gathering representative workloads manually. In this demonstration, we show an alternative approach to the physical ...
- research-articleDecember 2006
Generating Queries with Cardinality Constraints for DBMS Testing
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 18, Issue 12December 2006, Pages 1721–1725https://doi.org/10.1109/TKDE.2006.190Good testing coverage of novel database techniques, such as multidimensional histograms or changes in the execution engine, is a complex problem. In this work, we argue that this task requires generating query instances, not randomly, but based on a ...
- ArticleSeptember 2006
To tune or not to tune?: a lightweight physical design alerter
VLDB '06: Proceedings of the 32nd international conference on Very large data basesSeptember 2006, Pages 499–510In recent years there has been considerable research on automating the physical design in database systems. Current techniques provide good recommendations, but are resource intensive. This makes DBAs somewhat conservative when deciding to launch a ...
- ArticleMarch 2006
Physical design refinement: the "merge-reduce" approach
EDBT'06: Proceedings of the 10th international conference on Advances in Database TechnologyMarch 2006, Pages 386–404https://doi.org/10.1007/11687238_25Physical database design tools rely on a DBA-provided workload to pick an “optimal” set of indexes and materialized views. Such an approach fails to capture scenarios where DBAs are unable to produce a succinct workload for an automated tool but still ...
- ArticleAugust 2005
Flexible database generators
VLDB '05: Proceedings of the 31st international conference on Very large data basesAugust 2005, Pages 1097–1107Evaluation and applicability of many database techniques, ranging from access methods, histograms, and optimization strategies to data normalization and mining, crucially depend on their ability to cope with varying data distributions in a robust way. ...
- ArticleJune 2005
Automatic physical database tuning: a relaxation-based approach
SIGMOD '05: Proceedings of the 2005 ACM SIGMOD international conference on Management of dataJune 2005, Pages 227–238https://doi.org/10.1145/1066157.1066184In recent years there has been considerable research on automated selection of physical design in database systems. In current solutions, candidate access paths are heuristically chosen based on the structure of each input query, and a subsequent bottom-...
- ArticleJune 2004
Conditional selectivity for statistics on query expressions
SIGMOD '04: Proceedings of the 2004 ACM SIGMOD international conference on Management of dataJune 2004, Pages 311–322https://doi.org/10.1145/1007568.1007604Cardinality estimation during query optimization relies on simplifying assumptions that usually do not hold in practice. To diminish the impact of inaccurate estimates during optimization, statistics on query expressions (SITs) have been previously ...
- ArticleJune 2002
Exploiting statistics on query expressions for optimization
SIGMOD '02: Proceedings of the 2002 ACM SIGMOD international conference on Management of dataJune 2002, Pages 263–274https://doi.org/10.1145/564691.564722Statistics play an important role in influencing the plans produced by a query optimizer. Traditionally, optimizers use statistics built over base tables and assume independence between attributes while propagating statistical information through the ...
- articleJune 2002
Top-k selection queries over relational databases: Mapping strategies and performance evaluation
ACM Transactions on Database Systems (TODS), Volume 27, Issue 2Pages 153–187https://doi.org/10.1145/568518.568519In many applications, users specify target values for certain attributes, without requiring exact matches to these values in return. Instead, the result to such queries is typically a rank of the "top k" tuples that best match the given attribute ...
- ArticleMay 2001
STHoles: a multidimensional workload-aware histogram
SIGMOD '01: Proceedings of the 2001 ACM SIGMOD international conference on Management of dataMay 2001, Pages 211–222https://doi.org/10.1145/375663.375686Attributes of a relation are not typically independent. Multidimensional histograms can be an effective tool for accurate multiattribute query selectivity estimation. In this paper, we introduce STHoles, a “workload-aware” histogram that allows bucket ...
Also Published in:
ACM SIGMOD Record: Volume 30 Issue 2, June 2001