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H-store: A high-performance, distributed main memory transaction processing system

H-store: A high-performance, distributed main memory transaction processing system. Robert Kallman, Hideaki Kimura, Jonathan Natkins, Andrew Pavlo, Alex Rasin, Stanley B. Zdonik , Evan P. C. Jones, Samuel Madden, Michael Stonebraker, Yang Zhang, John Hugg, Daniel J. Abadi. Paper highlights.

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H-store: A high-performance, distributed main memory transaction processing system

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  1. H-store: A high-performance, distributed main memory transaction processing system Robert Kallman, Hideaki Kimura, Jonathan Natkins, Andrew Pavlo, Alex Rasin, Stanley B. Zdonik,Evan P. C. Jones, Samuel Madden, Michael Stonebraker, Yang Zhang, John Hugg, Daniel J. Abadi

  2. Paper highlights • An experimental main-memory, parallel DBMS • Optimized for on-line transaction processing (OLTP) applications • Highly distributed, row-store-based relational database • Runs on a cluster on shared-nothing, main memory executor nodes.

  3. Background

  4. Relational DBMS • Data are stored in tables • Each row corresponds to a record • No pointers or other links • Matching keys

  5. Barbara 13339 Student PSID 89 Mid 13339 Final PSID Major Alan 08887 87 08887 CS 89 90 CE Example • PSID is a key • Links rows among tables • Must be unique

  6. Atomic Transactions: You buy a car

  7. What are atomic transactions? • A mechanism used in databases and other financial systems. • System guarantees that an atomic transaction will either be executed properly or abort without leaving any trace All or nothing semantics • Atomic transactions verify the four ACID properties

  8. The ACID properties Atomicity: All or nothing property Consistency: A transaction either brings the data in a new consistent state of data or returns them to their previous state Isolation: A transaction in process and not yet committed has no effect on any other transaction. Durability: Committed data are stored by the system in some kind of crash-proof storage

  9. Importance of atomic transactions • Atomicity and consistency properties guarantee that either the transaction is correct or will leave no traces • No partial updates • No incorrect updates • Isolation property allows concurrent execution of transactions • Much faster than serial execution • Durability property ensures transactions will not be lost

  10. Back to the paper

  11. Motivation • Legacy OLTP databases • Too many of their architectural components are old • Inherited from original System R • Mid-seventies! • Take advantage of recent trends • Multi-core architectures • Cheap abundant main memory • Dominant use of stored procedures

  12. The focus • Reject “one size fits all” approach • On-line transaction processing (OLTP) systems have specific proprieties • Repetitive short-lived transactions • Stored procedures • Sole focus of this work

  13. Main issue Rely on replication to minimizethe risk of data loss • Poor I/O performance of RDBMS • Their solution • Scale system “horizontally” • Partition responsibilities among multiple shared nothing machines • Store entire DB in the memory of a large cluster of server machines

  14. H-Store Next generation OLTP system Operates on a distributed cluster of shared nothing machines Coordinates the work of multiple single-threaded engines All data are always kept in main memory

  15. System Overview • H-Store • Cluster containing two or more computational nodes • Nodes • Single physical component that holds multiple sites • Sites • Normally run on a dedicated core • Single-threaded • Do not share any data structure or memory with any collocated site

  16. H-Store system architecture

  17. System deployment • Cluster deployment framework takes at inputs • A set of stored procedures • A database schema • A sample workload (used to optimize data layout) • A set of available sites in the cluster • Two-phase optimization • First optimize stored procedures as if the database was not distributed • Then come with distributed query plans

  18. Run-time model • All sites in the cluster are trusted • Any site is able to execute any OLTP application request • Execution plan is • Annotated with the locations of the target sites • Passed to a transaction manager • No shared data structures • Everything is single-threaded

  19. Database properties • Physical layout of DB specifically optimized to execute precompiled transactions • Not ad hoc queries • Can still be executed but could be very slow

  20. Transaction classes • Two important special cases • Single-Site Transactions • Can be entirely executed on a single site • Easy to send the transaction to one of the target sites • One-Shot Transactions • Each of is individual queries executes on a single site • Output of these queries is not reused as inputs for other queries • Easy to execute in parallel

  21. Physical layout • Replicate frequently-accessed or read-only tables on each site • Horizontal partition of tables • Partitions can be accessed in parallel • Collocate them with related data • Protect data against node failures • Important for in-memory DBs • k-safety • Number k of node failures DB must tolerate

  22. DB layout loader • Table Replication • Replicate all read-only tables on all sites • Data Partitioning • Divide horizontally each table into four disjoint partitions • Each partition is stored on two different sites • Accent is on parallelism • K-Safety • k = 2

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