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ETL APIs for handling Time Series #366

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ETL APIs for handling Time Series #366

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binhmop
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@binhmop binhmop commented Jun 30, 2016

Description and related tickets, documents

Implemented a set of basic ETL APIs for time series analysis including:

  • downsampling
  • compute column difference
  • compute moving average

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Breaking changes & backward compatible issues

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PR Progress

Make sure all checkboxes below are checked before merged

  • Merge check has no conflicts. PR checks passed.
  • Main reviewer approved
  • Optional reviewer approved

@nhanitvn nhanitvn changed the title [PE-2175] ETL APIs for handling Time Series ETL APIs for handling Time Series Jun 30, 2016

val manager = ddf.getManager.asInstanceOf[SparkDDFManager]
val res = manager.newDDFFromSparkDataFrame(newdf)
manager.addDDF(res)
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don't need to do this

this.mTimestampColumn = timestampColumn;
List<String> groupByCols = Lists.newArrayList(timestampColumn);
if (mTsIDColumn != null && !mTsIDColumn.isEmpty()) {
groupByCols.add(mTsIDColumn);
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mTsIDColumn shouldn't be added here, this method should only downsample based on timestampColumn.

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downsampling should be for each mTsIDColumn

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what is mTsIDColumn?

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ID of a time series

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