feat: Collection functions (#64) (PR #109)

* feat: Collection functions (#64) * fix map testing & add map tests * doc & refactor: todo scaladoc link (issue #135) Co-authored-by: Eduardo Ruiz <[email protected]>
hablapps · Jan 24, 2022 · 75f91dd · 75f91dd
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diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
@@ -19,7 +19,7 @@ jobs:
           PGP_SECRET: ${{ secrets.PGP_SECRET }}
           SONATYPE_PASSWORD: ${{ secrets.SONATYPE_PASSWORD }}
           SONATYPE_USERNAME: ${{ secrets.SONATYPE_USERNAME }}
-      - name: Test & coverage # TODO running tests twice
+      - name: Test & coverage
         run: sbt coverage core/test coverageReport coverageAggregate
       - uses: codecov/codecov-action@v2
         with:

diff --git a/core/src/main/scala/doric/sem/AggregationOps.scala b/core/src/main/scala/doric/sem/AggregationOps.scala
@@ -55,12 +55,6 @@ private[sem] trait AggregationOps
       * @example {{{
       *   // Compute the average for all numeric columns cubed by department and group.
       *   ds.cube("department".cname, "group".cname).avg()
-      *
-      *   // Compute the max age and average salary, cubed by department and gender.
-      *   ds.cube("department".cname, "gender".cname).agg(Map(
-      *     "salary" -> "avg",
-      *     "age" -> "max"
-      *   ))
       * }}}
       * @see [[doric.doc.DRelationalGroupedDataset]] for all the available aggregate functions.
       * @see [[org.apache.spark.sql.Dataset.cube(col1:* org.apache.spark.sql.Dataset.cube]]
@@ -91,14 +85,7 @@ private[sem] trait AggregationOps
       * @example {{{
       *   // Compute the average for all numeric columns rolled up by department and group.
       *   ds.rollup("department".cname, "group".cname).avg()
-      *
-      *   // Compute the max age and average salary, rolled up by department and gender.
-      *   ds.rollup("department".cname, "gender".cname).agg(Map(
-      *     "salary" -> "avg",
-      *     "age" -> "max"
-      *   ))
       * }}}
-      * @todo this example is not from doric
       * @see [[doric.doc.DRelationalGroupedDataset]] for all the available aggregate functions.
       * @see [[org.apache.spark.sql.Dataset.rollup(col1:* org.apache.spark.sql.Dataset.rollup]]
       * @group Group Dataframe operation