The Experts below are selected from a list of 39 Experts worldwide ranked by ideXlab platform
Sooyong Kang - One of the best experts on this subject based on the ideXlab platform.
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border collie a wait free read optimal algorithm for Database Logging on multicore hardware
International Conference on Management of Data, 2019Co-Authors: Jongbin Kim, Hyuck Han, Sooyong Kang, Hyeongwon Jang, Seohui Son, Hyungsoo JungAbstract:Actions changing the state of Databases are all logged with proper ordering being imposed. Database engines obeying this golden rule of Logging enforce total ordering on all events, and this poses challenges in addressing the scalability bottlenecks of Database Logging on multicore hardware. We reexamined the problem of Database Logging and realized that in any given log history, obtaining an upper bound on the size of a set that preserves the happen-before relation is the essence of the matter. Based on our understanding, we propose Border-Collie, a wait-free and read-optimal algorithm for Database Logging that finds such an upper bound even with some worker threads often being idle. We show that (1) Border-Collie always finds the largest set of logged events satisfying the condition in a finite number of steps (i.e., wait-free), (2) the number of logged events to be read is also minimal (i.e., read-optimal), and (3) both properties hold even with threads being in intermittent work. Experimental results demonstrated that Border-Collie proves our claims under various workloads; Border-Collie outperforms the state-of-the-art centralized Logging techniques (i.e., Eleda and ERMIA) by up to ~2X and exhibits almost the same throughput with much shorter commit latency than the state-of-the-art decentralized Logging techniques (i.e., Silo and FOEDUS).
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Scalable Database Logging for multicores
Proceedings of the VLDB Endowment, 2017Co-Authors: Hyungsoo Jung, Hyuck Han, Sooyong KangAbstract:Modern Databases, guaranteeing atomicity and durability, store transaction logs in a volatile, central log buffer and then flush the log buffer to non-volatile storage by the write-ahead Logging principle. Buffering logs in central log store has recently faced a severe multicore scalability problem, and log flushing has been challenged by synchronous I/O delay. We have designed and implemented a fast and scalable Logging method, Eleda, that can migrate a surge of transaction logs from volatile memory to stable storage without risking durable transaction atomicity. Our efficient implementation of Eleda is enabled by a highly concurrent data structure, Grasshopper, that eliminates a multicore scalability problem of centralized Logging and enhances system utilization in the presence of synchronous I/O delay. We implemented Eleda and plugged it to WiredTiger and Shore-MT by replacing their log managers. Our evaluation showed that Eleda-based transaction systems improve performance up to 71 x, thus showing the applicability of Eleda.
Hyungsoo Jung - One of the best experts on this subject based on the ideXlab platform.
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border collie a wait free read optimal algorithm for Database Logging on multicore hardware
International Conference on Management of Data, 2019Co-Authors: Jongbin Kim, Hyuck Han, Sooyong Kang, Hyeongwon Jang, Seohui Son, Hyungsoo JungAbstract:Actions changing the state of Databases are all logged with proper ordering being imposed. Database engines obeying this golden rule of Logging enforce total ordering on all events, and this poses challenges in addressing the scalability bottlenecks of Database Logging on multicore hardware. We reexamined the problem of Database Logging and realized that in any given log history, obtaining an upper bound on the size of a set that preserves the happen-before relation is the essence of the matter. Based on our understanding, we propose Border-Collie, a wait-free and read-optimal algorithm for Database Logging that finds such an upper bound even with some worker threads often being idle. We show that (1) Border-Collie always finds the largest set of logged events satisfying the condition in a finite number of steps (i.e., wait-free), (2) the number of logged events to be read is also minimal (i.e., read-optimal), and (3) both properties hold even with threads being in intermittent work. Experimental results demonstrated that Border-Collie proves our claims under various workloads; Border-Collie outperforms the state-of-the-art centralized Logging techniques (i.e., Eleda and ERMIA) by up to ~2X and exhibits almost the same throughput with much shorter commit latency than the state-of-the-art decentralized Logging techniques (i.e., Silo and FOEDUS).
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Scalable Database Logging for multicores
Proceedings of the VLDB Endowment, 2017Co-Authors: Hyungsoo Jung, Hyuck Han, Sooyong KangAbstract:Modern Databases, guaranteeing atomicity and durability, store transaction logs in a volatile, central log buffer and then flush the log buffer to non-volatile storage by the write-ahead Logging principle. Buffering logs in central log store has recently faced a severe multicore scalability problem, and log flushing has been challenged by synchronous I/O delay. We have designed and implemented a fast and scalable Logging method, Eleda, that can migrate a surge of transaction logs from volatile memory to stable storage without risking durable transaction atomicity. Our efficient implementation of Eleda is enabled by a highly concurrent data structure, Grasshopper, that eliminates a multicore scalability problem of centralized Logging and enhances system utilization in the presence of synchronous I/O delay. We implemented Eleda and plugged it to WiredTiger and Shore-MT by replacing their log managers. Our evaluation showed that Eleda-based transaction systems improve performance up to 71 x, thus showing the applicability of Eleda.
Hyuck Han - One of the best experts on this subject based on the ideXlab platform.
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border collie a wait free read optimal algorithm for Database Logging on multicore hardware
International Conference on Management of Data, 2019Co-Authors: Jongbin Kim, Hyuck Han, Sooyong Kang, Hyeongwon Jang, Seohui Son, Hyungsoo JungAbstract:Actions changing the state of Databases are all logged with proper ordering being imposed. Database engines obeying this golden rule of Logging enforce total ordering on all events, and this poses challenges in addressing the scalability bottlenecks of Database Logging on multicore hardware. We reexamined the problem of Database Logging and realized that in any given log history, obtaining an upper bound on the size of a set that preserves the happen-before relation is the essence of the matter. Based on our understanding, we propose Border-Collie, a wait-free and read-optimal algorithm for Database Logging that finds such an upper bound even with some worker threads often being idle. We show that (1) Border-Collie always finds the largest set of logged events satisfying the condition in a finite number of steps (i.e., wait-free), (2) the number of logged events to be read is also minimal (i.e., read-optimal), and (3) both properties hold even with threads being in intermittent work. Experimental results demonstrated that Border-Collie proves our claims under various workloads; Border-Collie outperforms the state-of-the-art centralized Logging techniques (i.e., Eleda and ERMIA) by up to ~2X and exhibits almost the same throughput with much shorter commit latency than the state-of-the-art decentralized Logging techniques (i.e., Silo and FOEDUS).
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Scalable Database Logging for multicores
Proceedings of the VLDB Endowment, 2017Co-Authors: Hyungsoo Jung, Hyuck Han, Sooyong KangAbstract:Modern Databases, guaranteeing atomicity and durability, store transaction logs in a volatile, central log buffer and then flush the log buffer to non-volatile storage by the write-ahead Logging principle. Buffering logs in central log store has recently faced a severe multicore scalability problem, and log flushing has been challenged by synchronous I/O delay. We have designed and implemented a fast and scalable Logging method, Eleda, that can migrate a surge of transaction logs from volatile memory to stable storage without risking durable transaction atomicity. Our efficient implementation of Eleda is enabled by a highly concurrent data structure, Grasshopper, that eliminates a multicore scalability problem of centralized Logging and enhances system utilization in the presence of synchronous I/O delay. We implemented Eleda and plugged it to WiredTiger and Shore-MT by replacing their log managers. Our evaluation showed that Eleda-based transaction systems improve performance up to 71 x, thus showing the applicability of Eleda.
Yun Wang - One of the best experts on this subject based on the ideXlab platform.
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high performance Database Logging using storage class memory
International Conference on Data Engineering, 2011Co-Authors: Ru Fang, Huii Hsiao, Chandrasekaran Mohan, Yun WangAbstract:Storage class memory (SCM), a new generation of memory technology, offers non-volatility, high-speed, and byte-addressability, which combines the best properties of current hard disk drives (HDD) and main memory. With these extraordinary features, current systems and software stacks need to be redesigned to get significantly improved performance by eliminating disk input/output (I/O) barriers; and simpler system designs by avoiding complicated data format transformations. In current DBMSs, Logging and recovery are the most important components to enforce the atomicity and durability of a Database. Traditionally, Database systems rely on disks for Logging transaction actions and log records are forced to disks when a transaction commits. Because of the slow disk I/O speed, Logging becomes one of the major bottlenecks for a DBMS. Exploiting SCM as a persistent memory for transaction Logging can significantly reduce Logging overhead. In this paper, we present the detailed design of an SCM-based approach for DBMSs Logging, which achieves high performance by simplified system design and better concurrency support. We also discuss solutions to tackle several major issues arising during system recovery, including hole detection, partial write detection, and any-point failure recovery. This new Logging approach is used to replace the traditional disk based Logging approach in DBMSs. To analyze the performance characteristics of our SCM-based Logging approach, we implement the prototype on IBM SolidDB. In common circumstances, our experimental results show that the new SCM-based Logging approach provides as much as 7 times throughput improvement over disk-based Logging in the Telecommunication Application Transaction Processing (TATP) benchmark.
Ru Fang - One of the best experts on this subject based on the ideXlab platform.
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high performance Database Logging using storage class memory
International Conference on Data Engineering, 2011Co-Authors: Ru Fang, Huii Hsiao, Chandrasekaran Mohan, Yun WangAbstract:Storage class memory (SCM), a new generation of memory technology, offers non-volatility, high-speed, and byte-addressability, which combines the best properties of current hard disk drives (HDD) and main memory. With these extraordinary features, current systems and software stacks need to be redesigned to get significantly improved performance by eliminating disk input/output (I/O) barriers; and simpler system designs by avoiding complicated data format transformations. In current DBMSs, Logging and recovery are the most important components to enforce the atomicity and durability of a Database. Traditionally, Database systems rely on disks for Logging transaction actions and log records are forced to disks when a transaction commits. Because of the slow disk I/O speed, Logging becomes one of the major bottlenecks for a DBMS. Exploiting SCM as a persistent memory for transaction Logging can significantly reduce Logging overhead. In this paper, we present the detailed design of an SCM-based approach for DBMSs Logging, which achieves high performance by simplified system design and better concurrency support. We also discuss solutions to tackle several major issues arising during system recovery, including hole detection, partial write detection, and any-point failure recovery. This new Logging approach is used to replace the traditional disk based Logging approach in DBMSs. To analyze the performance characteristics of our SCM-based Logging approach, we implement the prototype on IBM SolidDB. In common circumstances, our experimental results show that the new SCM-based Logging approach provides as much as 7 times throughput improvement over disk-based Logging in the Telecommunication Application Transaction Processing (TATP) benchmark.
