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Copy file name to clipboardExpand all lines: lsm-tree.cabal
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* Basic key–value operations, such as lookup, insert, and delete.
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* Range lookups, which efficiently retrieve the values for all keys in a given range.
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* Monoidal upserts which combine the stored and new values.
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* BLOB storage which assocates a large auxiliary BLOB with a key.
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* BLOB storage which associates a large auxiliary BLOB with a key.
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* Durable on-disk persistence and rollback via named snapshots.
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* Cheap table duplication where all duplicates can be independently accessed and modified.
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* High-performance lookups on SSDs using I\/O batching and parallelism.
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* Each session locks its session directory.
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This means that a database cannot be accessed from different processes at the same time.
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* Tables can be used concurrently and concurrent use of read operations such as lookups is determinstic.
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* Tables can be used concurrently and concurrent use of read operations such as lookups is deterministic.
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However, concurrent use of write operations such as insert or delete with any other operation results in a race condition.
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== Performance #performance#
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An ordinary index stores the maximum serialised key for each memory page.
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The total in-memory size of all indexes is proportional to the average size of one serialised key per memory page.
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[@CompactIndex@]:
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A compact index stores the 64 most significant bits of the minimum serialised key for each memory page, as well as 1 bit per memory page to resolve clashes, 1 bit per memory page to mark overflow pages, and a negligable amount of memory for tie breakers.
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A compact index stores the 64 most significant bits of the minimum serialised key for each memory page, as well as 1 bit per memory page to resolve clashes, 1 bit per memory page to mark overflow pages, and a negligible amount of memory for tie breakers.
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The total in-memory size of all indexes is approximately 66 bits per memory page.
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The total size of an LSM-tree must not exceed \(2^{41}\) physical entries.
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