English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we study the problem of discovering join FDs, i.e., functionaldependencies (FDs) that hold on multiple joined tables. We leverage logicalinference, selective mining, and sampling and show that we can discover most ofthe exact join FDs from the single tables participating to the join and avoidthe full computation of the join result. We propose algorithms to speed-up thejoin FD discovery process and mine FDs on the fly only from necessary datapartitions. We introduce JEDI (Join dEpendency DIscovery), our solution todiscover join FDs without computation of the full join beforehand. Ourexperiments on a range of real-world and synthetic data demonstrate thebenefits of our method over existing FD discovery methods that need toprecompute the join results before discovering the FDs. We show that theperformance depends on the cardinalities and coverage of the join attributevalues: for join operations with low coverage, JEDI with selective miningoutperforms the competing methods using the straightforward approach of fulljoin computation by one order of magnitude in terms of runtime and can discoverthree-quarters of the exact join FDs using mainly logical inference in half ofits total execution time on average. For higher join coverage, JEDI withsampling reaches precision of 1 with only 63% of the table input size onaverage.

Discovering Multi-Table Functional Dependencies Without Full Join Computation