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  • Database_Internals_Alex_Petrov PDF 下载

    Database_Internals_Alex_Petrov PDF 下载

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    The primary job of any database management system is reliably storing
    data and making it available for users. We use databases as a primary
    source of data, helping us to share it between the different parts of our
    applications. Instead of finding a way to store and retrieve information
    and inventing a new way to organize data every time we create a new
    app, we use databases. This way we can concentrate on application logic
    instead of infrastructure.
    Since the term database management system (DBMS) is quite bulky,
    throughout this book we use more compact terms, database system and
    database, to refer to the same concept.
    Databases are modular systems and consist of multiple parts: a transport
    layer accepting requests, a query processor determining the most
    efficient way to run queries, an execution engine carrying out the
    operations, and a storage engine (see “DBMS Architecture”).
    The storage engine (or database engine) is a software component of a
    database management system responsible for storing, retrieving, and
    managing data in memory and on disk, designed to capture a persistent,
    long-term memory of each node [REED78]. While databases can
    respond to complex queries, storage engines look at the data more
    granularly and offer a simple data manipulation API, allowing users to
    create, update, delete, and retrieve records. One way to look at this is that
    database management systems are applications built on top of storage
    engines, offering a schema, a query language, indexing, transactions, and
    many other useful features.
    For flexibility, both keys and values can be arbitrary sequences of bytes
    with no prescribed form. Their sorting and representation semantics are
    defined in higher-level subsystems. For example, you can use int32 (32-
    bit integer) as a key in one of the tables, and ascii (ASCII string) in the
    other; from the storage engine perspective both keys are just serialized
    entries.
    Storage engines such as BerkeleyDB, LevelDB and its descendant
    RocksDB, LMDB and its descendant libmdbx, Sophia, HaloDB, and
    many others were developed independently from the database
    management systems they’re now embedded into. Using pluggable
    storage engines has enabled database developers to bootstrap database
    systems using existing storage engines, and concentrate on the other
    subsystems.
    At the same time, clear separation between database system components
    opens up an opportunity to switch between different engines, potentially
    better suited for particular use cases. For example, MySQL, a popular
    database management system, has several storage engines, including
    InnoDB, MyISAM, and RocksDB (in the MyRocks distribution).
    MongoDB allows switching between WiredTiger, In-Memory, and the
    (now-deprecated) MMAPv1 storage engines

     

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