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Preventing staleness in query results when using asynchronously updated indexes

  • US 10,606,839 B2
  • Filed: 05/23/2017
  • Issued: 03/31/2020
  • Est. Priority Date: 10/27/2015
  • Status: Active Grant
First Claim
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1. A computer implemented method, the method comprising:

  • receiving, by one or more processors, an asynchronously updated index corresponding to a main dataset in a database system;

    receiving, by the one or more processors, time-sequenced log data of modifications made to the main dataset after a cutoff time of a last asynchronous index update, wherein the time-sequenced log data is read once by the database system for joining the main dataset with the time-sequenced log data and filtering out updated dataset entries and deleted dataset entries from the asynchronously updated index;

    receiving, by the one or more processors, from an end user, a proximity-based query directed to the main dataset;

    joining, by the one or more processors, the main dataset with the time-sequenced log data resulting in a first intermediate result comprising a first one or more entries of the main dataset made after the cutoff time;

    processing, by the one or more processors, the proximity-based query to determine a second one or more entries satisfying the proximity-based query by emulating a function of the last asynchronous index update resulting in a second intermediate result, wherein the second intermediate result includes updated and deleted entries of a base table that are retrieved by the proximity-based query using an outdated asynchronously updated index, wherein the processing the proximity-based query further comprises receiving a staleness acceptability criterion; and

    determining, based at least in part on the staleness acceptability criterion, that one or more query results are acceptable;

    filtering out, by the one or more processors, the updated dataset entries from the asynchronously updated index using the time-sequenced log data to generate a lookup table as index table;

    processing, by the one or more processors, the proximity-based query against the main dataset using the lookup table resulting in a third intermediate result; and

    building, by the one or more processors, a union of the second intermediate result and the third intermediate result, to generate a final result of the proximity-based query.

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