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Adaptive Merging on Phase Change Memory

Macyna Wojciech, Kukowski Michal

Fundamenta Informaticae

2022

Vol. 188 nr 2

103--126

Indexing is a well-known database technique used to facilitate data access and speed up query processing. Nevertheless, the construction and modification of indexes are very expensive. In traditional approaches, all records in the database table are equally covered by the index. It is not effective, since some records may be queried very often and some never. To avoid this problem, adaptive merging has been introduced. The key idea is to create an index adaptively and incrementally as a side-product of query processing. As a result, the database table is indexed partially depending on the query workload. This paper faces the problem of adaptive merging for phase change memory (PCM). The most important features of this memory type are limited write endurance and high write latency. As a consequence, adaptive merging should be investigated from the scratch. We solve this problem in two steps. First, we apply several PCM optimization techniques to the traditional adaptive merging approach. We prove that the proposed method (eAM) outperforms a traditional approach by 60%. After that, we invent the framework for adaptive merging (PAM) and propose a new variant of the PCM-optimized index. It further improves the system performance by 20% for databases where search queries interleave with data modifications.

Flash-Aware Storage of the Column Oriented Databases

Macyna Wojciech, Kukowski Michal

Fundamenta Informaticae

2020

Vol. 173, nr 1

47--72

Solid state disks become the very popular storage devices. Nonetheless, their architecture based on flash memory has some limitations. They suffer from poor random write performance, as the flash memory blocks must be erased before write. Nowadays, among many database models, the column-oriented databases have attracted the attention. In this model, the data from the particular columns of the database table are stored separately in the memory blocks. As a consequence, only such columns are derived from the memory which are necessary for query execution. In this way, I/O number is reduced, what drastically increases the database performance. This paper proposes a new storage method for the column oriented databases on solid state disks. In this method, the data from each column is stored as a separated structure, called Column-Flash tree (CF-tree). The table is always sorted by a particular column (or a set of columns). Due to utilizing fractional cascading and tree-like structure, the efficiency of update and search is obtained. The storage may be adjusted to the altering query pattern and disk characteristics by changing the height of the CF-tree and the capacity of its levels. In contrast to the other models, the approach may be applied to both read and write optimized databases.