[jira] [Created] (SPARK-18688) Interpolated time series join

["Jarno Seppanen (JIRA)" <ji...@apache.org>]

Jarno Seppanen created SPARK-18688:
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             Summary: Interpolated time series join
                 Key: SPARK-18688
                 URL: https://issues.apache.org/jira/browse/SPARK-18688
             Project: Spark
          Issue Type: Improvement
          Components: SQL
    Affects Versions: 2.0.2
            Reporter: Jarno Seppanen


Time series joins are very common in analytics tasks. A simple example would be joining the newest value of number of followers from data frame F with sessions from data frame S. Currently, a cross join is needed for such joins in Spark, making them practically impossible.

Example syntax:
{noformat}
SELECT l.account_id, l.time AS login_time, f.num_followers
FROM account_login l
LEFT JOIN follower_count_changed f
  ON (f.account_id = l.account_id
      AND l.time INTERPOLATE PREVIOUS VALUE f.time)
{noformat}

In essence, I'd like to have support for efficiently running joins like INTERPOLATE PREVIOUS VALUE joins in Vertica [1].

Thanks for your consideration,
Jarno

[1] https://my.vertica.com/docs/7.1.x/HTML/index.htm#Authoring/SQLReferenceManual/LanguageElements/Predicates/INTERPOLATE.htm




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