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The Suppose we have a table that contains one column of high-precision timestamps and a dozen or more columns of FLOAT64, each column being time-series data. The columns are formed from an outer join of several similar table such that for any given high precision timestamp only a subset of the columns have non-null data values. We want to transform that table by quantizing the timestamps and doing some kind of aggregation in each column over all of the non-null values in a given quantized time bucket. Does the |
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Unfortunately this functionality currently doesn't work. Logica compiles to SQL and I don't think BigQuery has constructs for this. If I have a similar task I use some other tools/hacks to turn the table into having a row for each cell of the matrix, turning name of the column into a field. Then apply Logica to result. I understand that this is far from ideal. |
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Unfortunately this functionality currently doesn't work. Logica compiles to SQL and I don't think BigQuery has constructs for this.
In the long term extending the language to allow this makes total sense to me.
If I have a similar task I use some other tools/hacks to turn the table into having a row for each cell of the matrix, turning name of the column into a field. Then apply Logica to result. I understand that this is far from ideal.