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    @Article{OJDB_2017v4i1n01_Lindstroem,
        title     = {An NVM Aware MariaDB Database System and Associated IO Workload on File Systems},
        author    = {Jan Lindstr{\"o}m and
                     Dhananjoy Das and
                     Nick Piggin and
                     Santhosh Konundinya and
                     Torben Mathiasen and
                     Nisha Talagala and
                     Dulcardo Arteaga},
        journal   = {Open Journal of Databases (OJDB)},
        issn      = {2199-3459},
        year      = {2017},
        volume    = {4},
        number    = {1},
        pages     = {1--21},
        url       = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194662},
        urn       = {urn:nbn:de:101:1-201705194662},
        publisher = {RonPub},
        bibsource = {RonPub},
        abstract = {MariaDB is a community-developed fork of the MySQL relational database management system and originally designed and implemented in order to use the traditional spinning disk architecture. With Non-Volatile memory (NVM) technology now in the forefront and main stream for server storage (Data centers), MariaDB addresses the need by adding support for NVM devices and introduces NVM Compression method. NVM Compression is a novel hybrid technique that combines application level compression with flash awareness for optimal performance and storage efficiency. Utilizing new interface primitives exported by Flash Translation Layers (FTLs), we leverage the garbage collection available in flash devices to optimize the capacity management required by compression systems. We implement NVM Compression in the popular MariaDB database and use variants of commonly available POSIX file system interfaces to provide the extended FTL capabilities to the user space application. The experimental results show that the hybrid approach of NVM Compression can improve compression performance by 2-7x, deliver compression performance for flash devices that is within 5\% of uncompressed performance, improve storage efficiency by 19\% over legacy Row-Compression, reduce data writes by up to 4x when combined with other flash aware techniques such as Atomic Writes, and deliver further advantages in power efficiency and CPU utilization. Various micro benchmark measurement and findings on sparse files call for required improvement in file systems for handling of punch hole operations on files.}
    }