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Techniques for evaluating query predicates during in-memory table scans

机译:在内存表扫描过程中评估查询谓词的技术

摘要

Techniques are described herein for filtering data from a table during an in-memory scan. Predicates are pushed to in-memory scan to avoid scanning unnecessary columnar units and reduce the overhead of decompressing, row stitching and distributing data during evaluation. Techniques are described herein for generating implied predicates that have conditions on single columns from complex predicates that have multiple conditions on the same column, which can be evaluated during an in-memory scan. Techniques are also described herein to reduce the overhead of a table scan for processing a join query. When redistributing a first table for performing a hash-join, the nodes performing an in-memory scan of the first table may create a filter that tracks unique values from the join key. Data from the second table is only processed and transferred to other nodes in the cluster if the values from the join key pass through the filter.
机译:本文描述了用于在内存中扫描期间从表中过滤数据的技术。将谓词推送到内存中扫描,以避免扫描不必要的列单元,并减少评估期间解压缩,行拼接和分发数据的开销。本文描述了用于从在同一列上具有多个条件的复杂谓词生成在单个列上具有条件的隐式谓词的技术,这些隐式谓词可以在内存扫描中进行评估。本文还描述了减少用于处理联接查询的表扫描的开销的技术。当重新分配用于执行哈希联接的第一表时,对第一表执行内存中扫描的节点可以创建一个过滤器,该过滤器跟踪来自联接键的唯一值。如果连接键中的值通过过滤器,则仅处理第二个表中的数据并将其传输到群集中的其他节点。

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