Details
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Improvement
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Status: Closed
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Major
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Resolution: Resolved
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Description
The initial implementation of temporal graph queries supported ten second time windows which is useful for log analytics use cases. This ticket will allow for event correlation across daily windows, which is useful for many different fields, including event correlation in the stock market
This ticket will add the support for daily windows and add the syntax to support other time windows as well. Follow-on tickets will add more time windows.
Below is the sample syntax for a temporal graph query with a window of 1 DAY.
nodes(daily_stock_returns, search(daily_stock_returns, q="ticker_s:jpm AND change_d:[2 TO *]", fl="day_s", sort="change_d desc", rows="50"), walk="day_s->day_s", gather="ticker_s", fq="change_d:[1 TO *]", window="1DAY", lag="2", count(*))
This query counts all tickers that are up by atleast 1, in a one day window, 2 days prior to a rise in the ticker jpm by atleast 2. This surfaces tickers that most frequently rise two days before jpm rises.
This demonstrates event correlation in stock market data.