The Experts below are selected from a list of 9 Experts worldwide ranked by ideXlab platform
Randall Weis - One of the best experts on this subject based on the ideXlab platform.
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Diagrams and Other Notations
Managing Time in Relational Databases, 2020Co-Authors: Tom Johnston, Randall WeisAbstract:This chapter introduces the schema common to all asserted version tables, as well as various diagrams, and notations. All of the concepts such as objects, episodes, versions, and assertions, and the two principal semantic constraints of temporal entity integrity and temporal referential integrity, are physically realized as rows in tables that are all based on the schema of asserted version tables. All asserted version tables have the same nonbusiness-data columns. All the other columns, such as row number, object identifier, effective begin date, effective end date, and effective end date are part of the syntax common to all asserted version tables, part of the bitemporal machinery of Asserted Versioning. For Asserted Versioning, it is necessary to have a row creation date which is distinct from the assertion begin date. The chapter presents diagrams that are used to illustrate Asserted Versioning. The “basic diagram” of an asserted version table contains five main components: current clock tick; a temporal insert, update or Delete Transaction; a calendar timeline covering approximately four years, in monthly increments; a stacked series of assertion time snapshots of the table; and the table itself, including all rows across all effective and assertion times. The chapter also explains how Asserted Versioning supports the dynamic views that hide the complexities of asserted version tables schema from query authors who would otherwise are likely be confused by the complexity.
Tom Johnston - One of the best experts on this subject based on the ideXlab platform.
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Diagrams and Other Notations
Managing Time in Relational Databases, 2020Co-Authors: Tom Johnston, Randall WeisAbstract:This chapter introduces the schema common to all asserted version tables, as well as various diagrams, and notations. All of the concepts such as objects, episodes, versions, and assertions, and the two principal semantic constraints of temporal entity integrity and temporal referential integrity, are physically realized as rows in tables that are all based on the schema of asserted version tables. All asserted version tables have the same nonbusiness-data columns. All the other columns, such as row number, object identifier, effective begin date, effective end date, and effective end date are part of the syntax common to all asserted version tables, part of the bitemporal machinery of Asserted Versioning. For Asserted Versioning, it is necessary to have a row creation date which is distinct from the assertion begin date. The chapter presents diagrams that are used to illustrate Asserted Versioning. The “basic diagram” of an asserted version table contains five main components: current clock tick; a temporal insert, update or Delete Transaction; a calendar timeline covering approximately four years, in monthly increments; a stacked series of assertion time snapshots of the table; and the table itself, including all rows across all effective and assertion times. The chapter also explains how Asserted Versioning supports the dynamic views that hide the complexities of asserted version tables schema from query authors who would otherwise are likely be confused by the complexity.
Ilyeop Yi - One of the best experts on this subject based on the ideXlab platform.
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Building social networking services systems using the relational shared-nothing parallel DBMS
Data & Knowledge Engineering, 2020Co-Authors: Kyu-young Whang, Inju Na, Jin-ah Park, Ilyeop YiAbstract:Abstract We propose methods to enable the relational model to meet scalability and functionality needs of a large-scale social networking services (SNS) system. NewSQL has emerged recently indicating that shared-nothing parallel relational DBMSs can be used to guarantee the ACID properties of Transactions while keeping the high scalability of NoSQL. Leading commercial SNS systems, however, rely on a graph – not relational – data model with key–value storage and, for certain operations, suffer overhead of unnecessarily accessing multiple system nodes. Exploiting higher semantics with the relational data model could be the remedy. The solution we offer aims to perform a Transaction as a set of independent local Transactions whenever possible based on the conceptual semantics of the SNS database schema. First, it hierarchically clusters entities that are sitting on a path of frequently navigated one-to-many relationships, thereby avoiding inter-node joins. Second, when a multi-node Delete Transaction is performed over many-to-many relationships, it defers deletion of related references until they are accessed later, thereby amortizing the cost of multi-node updates. These solutions have been implemented in Odysseus/SNS — an SNS system using a shared nothing parallel DBMS. Performance evaluation using synthetic workload that reflects the real SNS workload demonstrates significant improvement in processing time. We also note that our work is the first to present the entity-relationship schema and its relational representation of the SNS database.
Kyu-young Whang - One of the best experts on this subject based on the ideXlab platform.
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Building social networking services systems using the relational shared-nothing parallel DBMS
Data & Knowledge Engineering, 2020Co-Authors: Kyu-young Whang, Inju Na, Jin-ah Park, Ilyeop YiAbstract:Abstract We propose methods to enable the relational model to meet scalability and functionality needs of a large-scale social networking services (SNS) system. NewSQL has emerged recently indicating that shared-nothing parallel relational DBMSs can be used to guarantee the ACID properties of Transactions while keeping the high scalability of NoSQL. Leading commercial SNS systems, however, rely on a graph – not relational – data model with key–value storage and, for certain operations, suffer overhead of unnecessarily accessing multiple system nodes. Exploiting higher semantics with the relational data model could be the remedy. The solution we offer aims to perform a Transaction as a set of independent local Transactions whenever possible based on the conceptual semantics of the SNS database schema. First, it hierarchically clusters entities that are sitting on a path of frequently navigated one-to-many relationships, thereby avoiding inter-node joins. Second, when a multi-node Delete Transaction is performed over many-to-many relationships, it defers deletion of related references until they are accessed later, thereby amortizing the cost of multi-node updates. These solutions have been implemented in Odysseus/SNS — an SNS system using a shared nothing parallel DBMS. Performance evaluation using synthetic workload that reflects the real SNS workload demonstrates significant improvement in processing time. We also note that our work is the first to present the entity-relationship schema and its relational representation of the SNS database.
Inju Na - One of the best experts on this subject based on the ideXlab platform.
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Building social networking services systems using the relational shared-nothing parallel DBMS
Data & Knowledge Engineering, 2020Co-Authors: Kyu-young Whang, Inju Na, Jin-ah Park, Ilyeop YiAbstract:Abstract We propose methods to enable the relational model to meet scalability and functionality needs of a large-scale social networking services (SNS) system. NewSQL has emerged recently indicating that shared-nothing parallel relational DBMSs can be used to guarantee the ACID properties of Transactions while keeping the high scalability of NoSQL. Leading commercial SNS systems, however, rely on a graph – not relational – data model with key–value storage and, for certain operations, suffer overhead of unnecessarily accessing multiple system nodes. Exploiting higher semantics with the relational data model could be the remedy. The solution we offer aims to perform a Transaction as a set of independent local Transactions whenever possible based on the conceptual semantics of the SNS database schema. First, it hierarchically clusters entities that are sitting on a path of frequently navigated one-to-many relationships, thereby avoiding inter-node joins. Second, when a multi-node Delete Transaction is performed over many-to-many relationships, it defers deletion of related references until they are accessed later, thereby amortizing the cost of multi-node updates. These solutions have been implemented in Odysseus/SNS — an SNS system using a shared nothing parallel DBMS. Performance evaluation using synthetic workload that reflects the real SNS workload demonstrates significant improvement in processing time. We also note that our work is the first to present the entity-relationship schema and its relational representation of the SNS database.