The Experts below are selected from a list of 80472 Experts worldwide ranked by ideXlab platform

Heejin Park - One of the best experts on this subject based on the ideXlab platform.

  • using multiple indexes for efficient subsequence matching in time series Databases
    Information Sciences, 2007
    Co-Authors: Heejin Park
    Abstract:

    A time-series Database is a set of data sequences, each of which is a list of changing values of an object in a given period of time. Subsequence matching is an operation that searches for such data subsequences whose changing patterns are similar to a query sequence in a time-series Database. This paper addresses a performance issue of time-series subsequence matching. First, we quantitatively examine the performance degradation caused by the window size effect, and then show that the performance of subsequence matching with a single index is not satisfactory in real applications. We claim that index interpolation is a fairly effective tool to solve this problem. Index interpolation performs subsequence matching by selecting the most appropriate one from multiple indexes built on windows of their distinct sizes. For index interpolation, we need to decide the sizes of windows for multiple indexes to be built. In this paper, we solve the problem of selecting optimal window sizes from the perspective of Physical Database design. Given a set of pairs of query sequences to be performed in a target application and a set of window sizes for building multiple indexes, we devise a formula that estimates the overall cost of all the subsequence matchings performed in a target application. By using this formula, we propose an algorithm that determines the optimal window sizes for maximizing the performance of entire subsequence matchings. We formally prove the optimality as well as the effectiveness of the algorithm. Finally, we show the superiority of our approach by performing extensive experiments with a real-life stock data set and a large volume of synthetic data sets.

  • using multiple indexes for efficient subsequence matching in time series Databases
    Lecture Notes in Computer Science, 2006
    Co-Authors: Heejin Park
    Abstract:

    Time-series subsequence matching is an operation that searches for such data subsequences whose changing patterns are similar to a query sequence from a time-series Database. This paper addresses a performance issue of time-series subsequence matching. First, we quantitatively examine the performance degradation caused by the window size effect, and then show that the performance of subsequence matching with a single index is not satisfactory in real applications. We claim that index interpolation is a fairly effective tool to resolve this problem. Index interpolation performs subsequence matching by selecting the most appropriate one from multiple indexes built on windows of their distinct sizes. For index interpolation, we need to decide the sizes of windows for multiple indexes to be built. In this paper, we solve the problem of selecting optimal window sizes in the perspective of Physical Database design. For this, given a set of pairs (length, frequency) of query sequences to be performed in a target application and a set of window sizes for building multiple indexes, we devise a formula that estimates the overall cost of all the subsequence matchings. By using this formula, we propose an algorithm that determines the optimal window sizes for maximizing the performance of entire subsequence matchings. We formally prove the optimality as well as the effectiveness of the algorithm. Finally, we perform a series of experiments with a real-life stock data set and a large volume of a synthetic data set to show the superiority of our approach.

Manoj Syamala - One of the best experts on this subject based on the ideXlab platform.

  • compression aware Physical Database design
    arXiv: Databases, 2011
    Co-Authors: Hideaki Kimura, Vivek Narasayya, Manoj Syamala
    Abstract:

    Modern RDBMSs support the ability to compress data using methods such as null suppression and dictionary encoding. Data compression offers the promise of significantly reducing storage requirements and improving I/O performance for decision support queries. However, compression can also slow down update and query performance due to the CPU costs of compression and decompression. In this paper, we study how data compression affects choice of appropriate Physical Database design, such as indexes, for a given workload. We observe that approaches that decouple the decision of whether or not to choose an index from whether or not to compress the index can result in poor solutions. Thus, we focus on the novel problem of integrating compression into Physical Database design in a scalable manner. We have implemented our techniques by modifying Microsoft SQL Server and the Database Engine Tuning Advisor (DTA) Physical design tool. Our techniques are general and are potentially applicable to DBMSs that support other compression methods. Our experimental results on real world as well as TPC-H benchmark workloads demonstrate the effectiveness of our techniques.

  • Database tuning advisor for microsoft sql server 2005 demo
    International Conference on Management of Data, 2005
    Co-Authors: Sanjay Agrawal, Surajit Chaudhuri, Vivek Narasayya, Lubor Kollar, Arun Marathe, Manoj Syamala
    Abstract:

    Database Tuning Advisor (DTA) is a Physical Database design tool that is part of Microsoft's SQL Server 2005 relational Database management system. Previously known as "Index Tuning Wizard" in SQL Server 7.0 and SQL Server 2000, DTA adds new functionality that is not available in other contemporary Physical design tuning tools. Novel aspects of DTA that will be demonstrated include: (a) Ability to take into account both performance and manageability requirements of DBAs (b) Fully integrated recommendations for indexes, materialized views and horizontal partitioning (c) Transparently leverage a test server to offload tuning load from production server and (d) Easy programmability and scriptability.

  • Database tuning advisor
    2004
    Co-Authors: Alexander Raizman, Sanjay Agrawal, Lubor Kollar, Manoj Syamala, Arunprasad P Marathe, Djana Ophelia Clay Milton, Dmitry Sonkin, Maciej Sarnowicz, Raja S Duddupudi, Surajit Chaudhuri
    Abstract:

    An automated Physical Database design tool may provide an integrated Physical design recommendation for horizontal partitioning, indexes and indexed views, all three features being tuned together (in concert). Manageability requirements may be specified when optimizing for performance. User-specified configuration may enable the specification of a partial Physical design without materialization of the Physical design. The tuning process may be performed for a production server but may be conducted substantially on a test server. Secondary indexes may be suggested for XML columns. Tuning of a Database may be invoked by any owner of a Database. Usage of objects may be evaluated and a recommendation for dropping unused objects may be issued. Reports may be provided concerning the count and percentage of queries in the workload that reference a particular Database, and/or the count and percentage of queries in the workload that reference a particular table or column. A feature may be provided whereby a weight may be associated with each statement in the workload, enabling relative importance of particular statements to be specified. An in-row length for a column may be specified. If a value for the column exceeds the specified in-row length for that column, the portion of the value not exceeding the specified in-row length may be stored in the row while the portion of the value exceeding the specified in-row length may be stored in an overflow area. Rebuild and reorganization recommendations may be generated.

  • Database tuning advisor for microsoft sql server 2005
    Very Large Data Bases, 2004
    Co-Authors: Sanjay Agrawal, Surajit Chaudhuri, Vivek Narasayya, Lubor Kollar, Arunprasad P Marathe, Manoj Syamala
    Abstract:

    Publisher Summary This chapter provides an overview of Database Tuning Advisor's (DTA's) novel functionality, the rationale for its architecture, and demonstrates DTA's quality and scalability on large customer workloads. The DTA is part of Microsoft SQL Server 2005. It is an automated Physical Database design tool that significantly advances the state-of-the-art in several ways. First, the DTA is capable of providing an integrated Physical design recommendation for horizontal partitioning, indexes, and materialized views. Second, unlike today's Physical design tools that focus solely on performance, the DTA also supports the capability for a Database administrator (DBA) to specify manageability requirements while optimizing for performance. Third, the DTA is able to scale to large Databases and workloads using several novel techniques including: workload compression, reduced statistics creation, and exploiting test server to reduce load on production server. Finally, the DTA greatly enhances scriptability and customization through the use of a public XML schema for input and output.

Surajit Chaudhuri - One of the best experts on this subject based on the ideXlab platform.

  • Self-tuning Database systems: a decade of progress
    VLDB, 2007
    Co-Authors: Surajit Chaudhuri, Vivek R Narasayya
    Abstract:

    In this paper we discuss advances in self-tuning Database systems over the past decade, based on our experience in the AutoAdmin project at Microsoft Research. This paper primarily focuses on the problem of automated Physical Database design. We also highlight other areas where research on self-tuning Database technology has made significant progress. We conclude with our thoughts on opportunities and open issues.

  • Database tuning advisor for microsoft sql server 2005 demo
    International Conference on Management of Data, 2005
    Co-Authors: Sanjay Agrawal, Surajit Chaudhuri, Vivek Narasayya, Lubor Kollar, Arun Marathe, Manoj Syamala
    Abstract:

    Database Tuning Advisor (DTA) is a Physical Database design tool that is part of Microsoft's SQL Server 2005 relational Database management system. Previously known as "Index Tuning Wizard" in SQL Server 7.0 and SQL Server 2000, DTA adds new functionality that is not available in other contemporary Physical design tuning tools. Novel aspects of DTA that will be demonstrated include: (a) Ability to take into account both performance and manageability requirements of DBAs (b) Fully integrated recommendations for indexes, materialized views and horizontal partitioning (c) Transparently leverage a test server to offload tuning load from production server and (d) Easy programmability and scriptability.

  • automatic Physical Database tuning a relaxation based approach
    International Conference on Management of Data, 2005
    Co-Authors: Nicolas Bruno, Surajit Chaudhuri
    Abstract:

    In 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-up search is performed to identify the best overall configuration. To handle large workloads and multiple kinds of Physical structures, recent techniques have become increasingly complex: they exhibit many special cases, shortcuts, and heuristics that make it very difficult to analyze and extract properties. In this paper we critically examine the architecture of current solutions. We then design a new framework for the Physical design problem that significantly reduces the assumptions and heuristics used in previous approaches. While simplicity and uniformity are important contributions in themselves, we report extensive experimental results showing that our approach could result in comparable (and, in many cases, considerably better) recommendations than state-of-the-art commercial alternatives.

  • Database tuning advisor
    2004
    Co-Authors: Alexander Raizman, Sanjay Agrawal, Lubor Kollar, Manoj Syamala, Arunprasad P Marathe, Djana Ophelia Clay Milton, Dmitry Sonkin, Maciej Sarnowicz, Raja S Duddupudi, Surajit Chaudhuri
    Abstract:

    An automated Physical Database design tool may provide an integrated Physical design recommendation for horizontal partitioning, indexes and indexed views, all three features being tuned together (in concert). Manageability requirements may be specified when optimizing for performance. User-specified configuration may enable the specification of a partial Physical design without materialization of the Physical design. The tuning process may be performed for a production server but may be conducted substantially on a test server. Secondary indexes may be suggested for XML columns. Tuning of a Database may be invoked by any owner of a Database. Usage of objects may be evaluated and a recommendation for dropping unused objects may be issued. Reports may be provided concerning the count and percentage of queries in the workload that reference a particular Database, and/or the count and percentage of queries in the workload that reference a particular table or column. A feature may be provided whereby a weight may be associated with each statement in the workload, enabling relative importance of particular statements to be specified. An in-row length for a column may be specified. If a value for the column exceeds the specified in-row length for that column, the portion of the value not exceeding the specified in-row length may be stored in the row while the portion of the value exceeding the specified in-row length may be stored in an overflow area. Rebuild and reorganization recommendations may be generated.

  • Database tuning advisor for microsoft sql server 2005
    Very Large Data Bases, 2004
    Co-Authors: Sanjay Agrawal, Surajit Chaudhuri, Vivek Narasayya, Lubor Kollar, Arunprasad P Marathe, Manoj Syamala
    Abstract:

    Publisher Summary This chapter provides an overview of Database Tuning Advisor's (DTA's) novel functionality, the rationale for its architecture, and demonstrates DTA's quality and scalability on large customer workloads. The DTA is part of Microsoft SQL Server 2005. It is an automated Physical Database design tool that significantly advances the state-of-the-art in several ways. First, the DTA is capable of providing an integrated Physical design recommendation for horizontal partitioning, indexes, and materialized views. Second, unlike today's Physical design tools that focus solely on performance, the DTA also supports the capability for a Database administrator (DBA) to specify manageability requirements while optimizing for performance. Third, the DTA is able to scale to large Databases and workloads using several novel techniques including: workload compression, reduced statistics creation, and exploiting test server to reduce load on production server. Finally, the DTA greatly enhances scriptability and customization through the use of a public XML schema for input and output.

Sanjay Agrawal - One of the best experts on this subject based on the ideXlab platform.

  • Database tuning advisor for microsoft sql server 2005 demo
    International Conference on Management of Data, 2005
    Co-Authors: Sanjay Agrawal, Surajit Chaudhuri, Vivek Narasayya, Lubor Kollar, Arun Marathe, Manoj Syamala
    Abstract:

    Database Tuning Advisor (DTA) is a Physical Database design tool that is part of Microsoft's SQL Server 2005 relational Database management system. Previously known as "Index Tuning Wizard" in SQL Server 7.0 and SQL Server 2000, DTA adds new functionality that is not available in other contemporary Physical design tuning tools. Novel aspects of DTA that will be demonstrated include: (a) Ability to take into account both performance and manageability requirements of DBAs (b) Fully integrated recommendations for indexes, materialized views and horizontal partitioning (c) Transparently leverage a test server to offload tuning load from production server and (d) Easy programmability and scriptability.

  • Database tuning advisor
    2004
    Co-Authors: Alexander Raizman, Sanjay Agrawal, Lubor Kollar, Manoj Syamala, Arunprasad P Marathe, Djana Ophelia Clay Milton, Dmitry Sonkin, Maciej Sarnowicz, Raja S Duddupudi, Surajit Chaudhuri
    Abstract:

    An automated Physical Database design tool may provide an integrated Physical design recommendation for horizontal partitioning, indexes and indexed views, all three features being tuned together (in concert). Manageability requirements may be specified when optimizing for performance. User-specified configuration may enable the specification of a partial Physical design without materialization of the Physical design. The tuning process may be performed for a production server but may be conducted substantially on a test server. Secondary indexes may be suggested for XML columns. Tuning of a Database may be invoked by any owner of a Database. Usage of objects may be evaluated and a recommendation for dropping unused objects may be issued. Reports may be provided concerning the count and percentage of queries in the workload that reference a particular Database, and/or the count and percentage of queries in the workload that reference a particular table or column. A feature may be provided whereby a weight may be associated with each statement in the workload, enabling relative importance of particular statements to be specified. An in-row length for a column may be specified. If a value for the column exceeds the specified in-row length for that column, the portion of the value not exceeding the specified in-row length may be stored in the row while the portion of the value exceeding the specified in-row length may be stored in an overflow area. Rebuild and reorganization recommendations may be generated.

  • integrating vertical and horizontal partitioning into automated Physical Database design
    International Conference on Management of Data, 2004
    Co-Authors: Sanjay Agrawal, Vivek Narasayya, Beverly Yang
    Abstract:

    In addition to indexes and materialized views, horizontal and vertical partitioning are important aspects of Physical design in a relational Database system that significantly impact performance. Horizontal partitioning also provides manageability; Database administrators often require indexes and their underlying tables partitioned identically so as to make common operations such as backup/restore easier. While partitioning is important, incorporating partitioning makes the problem of automating Physical design much harder since: (a) The choices of partitioning can strongly interact with choices of indexes and materialized views. (b) A large new space of Physical design alternatives must be considered. (c) Manageability requirements impose a new constraint on the problem. In this paper, we present novel techniques for designing a scalable solution to this integrated Physical design problem that takes both performance and manageability into account. We have implemented our techniques and evaluated it on Microsoft SQL Server. Our experiments highlight: (a) the importance of taking an integrated approach to automated Physical design and (b) the scalability of our techniques.

  • Database tuning advisor for microsoft sql server 2005
    Very Large Data Bases, 2004
    Co-Authors: Sanjay Agrawal, Surajit Chaudhuri, Vivek Narasayya, Lubor Kollar, Arunprasad P Marathe, Manoj Syamala
    Abstract:

    Publisher Summary This chapter provides an overview of Database Tuning Advisor's (DTA's) novel functionality, the rationale for its architecture, and demonstrates DTA's quality and scalability on large customer workloads. The DTA is part of Microsoft SQL Server 2005. It is an automated Physical Database design tool that significantly advances the state-of-the-art in several ways. First, the DTA is capable of providing an integrated Physical design recommendation for horizontal partitioning, indexes, and materialized views. Second, unlike today's Physical design tools that focus solely on performance, the DTA also supports the capability for a Database administrator (DBA) to specify manageability requirements while optimizing for performance. Third, the DTA is able to scale to large Databases and workloads using several novel techniques including: workload compression, reduced statistics creation, and exploiting test server to reduce load on production server. Finally, the DTA greatly enhances scriptability and customization through the use of a public XML schema for input and output.

Vivek Narasayya - One of the best experts on this subject based on the ideXlab platform.

  • compression aware Physical Database design
    arXiv: Databases, 2011
    Co-Authors: Hideaki Kimura, Vivek Narasayya, Manoj Syamala
    Abstract:

    Modern RDBMSs support the ability to compress data using methods such as null suppression and dictionary encoding. Data compression offers the promise of significantly reducing storage requirements and improving I/O performance for decision support queries. However, compression can also slow down update and query performance due to the CPU costs of compression and decompression. In this paper, we study how data compression affects choice of appropriate Physical Database design, such as indexes, for a given workload. We observe that approaches that decouple the decision of whether or not to choose an index from whether or not to compress the index can result in poor solutions. Thus, we focus on the novel problem of integrating compression into Physical Database design in a scalable manner. We have implemented our techniques by modifying Microsoft SQL Server and the Database Engine Tuning Advisor (DTA) Physical design tool. Our techniques are general and are potentially applicable to DBMSs that support other compression methods. Our experimental results on real world as well as TPC-H benchmark workloads demonstrate the effectiveness of our techniques.

  • Database tuning advisor for microsoft sql server 2005 demo
    International Conference on Management of Data, 2005
    Co-Authors: Sanjay Agrawal, Surajit Chaudhuri, Vivek Narasayya, Lubor Kollar, Arun Marathe, Manoj Syamala
    Abstract:

    Database Tuning Advisor (DTA) is a Physical Database design tool that is part of Microsoft's SQL Server 2005 relational Database management system. Previously known as "Index Tuning Wizard" in SQL Server 7.0 and SQL Server 2000, DTA adds new functionality that is not available in other contemporary Physical design tuning tools. Novel aspects of DTA that will be demonstrated include: (a) Ability to take into account both performance and manageability requirements of DBAs (b) Fully integrated recommendations for indexes, materialized views and horizontal partitioning (c) Transparently leverage a test server to offload tuning load from production server and (d) Easy programmability and scriptability.

  • integrating vertical and horizontal partitioning into automated Physical Database design
    International Conference on Management of Data, 2004
    Co-Authors: Sanjay Agrawal, Vivek Narasayya, Beverly Yang
    Abstract:

    In addition to indexes and materialized views, horizontal and vertical partitioning are important aspects of Physical design in a relational Database system that significantly impact performance. Horizontal partitioning also provides manageability; Database administrators often require indexes and their underlying tables partitioned identically so as to make common operations such as backup/restore easier. While partitioning is important, incorporating partitioning makes the problem of automating Physical design much harder since: (a) The choices of partitioning can strongly interact with choices of indexes and materialized views. (b) A large new space of Physical design alternatives must be considered. (c) Manageability requirements impose a new constraint on the problem. In this paper, we present novel techniques for designing a scalable solution to this integrated Physical design problem that takes both performance and manageability into account. We have implemented our techniques and evaluated it on Microsoft SQL Server. Our experiments highlight: (a) the importance of taking an integrated approach to automated Physical design and (b) the scalability of our techniques.

  • Database tuning advisor for microsoft sql server 2005
    Very Large Data Bases, 2004
    Co-Authors: Sanjay Agrawal, Surajit Chaudhuri, Vivek Narasayya, Lubor Kollar, Arunprasad P Marathe, Manoj Syamala
    Abstract:

    Publisher Summary This chapter provides an overview of Database Tuning Advisor's (DTA's) novel functionality, the rationale for its architecture, and demonstrates DTA's quality and scalability on large customer workloads. The DTA is part of Microsoft SQL Server 2005. It is an automated Physical Database design tool that significantly advances the state-of-the-art in several ways. First, the DTA is capable of providing an integrated Physical design recommendation for horizontal partitioning, indexes, and materialized views. Second, unlike today's Physical design tools that focus solely on performance, the DTA also supports the capability for a Database administrator (DBA) to specify manageability requirements while optimizing for performance. Third, the DTA is able to scale to large Databases and workloads using several novel techniques including: workload compression, reduced statistics creation, and exploiting test server to reduce load on production server. Finally, the DTA greatly enhances scriptability and customization through the use of a public XML schema for input and output.

  • autoadmin what if index analysis utility
    International Conference on Management of Data, 1998
    Co-Authors: Surajit Chaudhuri, Vivek Narasayya
    Abstract:

    As Databases get widely deployed, it becomes increasingly important to reduce the overhead of Database administration. An important aspect of data administration that critically influences performance is the ability to select indexes for a Database. In order to decide the right indexes for a Database, it is crucial for the Database administrator (DBA) to be able to perform a quantitative analysis of the existing indexes. Furthermore, the DBA should have the ability to propose hypothetical (“what-if”) indexes and quantitatively analyze their impact on performance of the system. Such impact analysis may consist of analyzing workloads over the Database, estimating changes in the cost of a workload, and studying index usage while taking into account projected changes in the sizes of the Database tables. In this paper we describe a novel index analysis utility that we have prototyped for Microsoft SQL Server 7.0. We describe the interfaces exposed by this utility that can be leveraged by a variety of front-end tools and sketch important aspects of the user interfaces enabled by the utility. We also discuss the implementation techniques for efficiently supporting “what-if” indexes. Our framework can be extended to incorporate analysis of other aspects of Physical Database design.