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Sample scala test
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package roger | |
import org.scalatest.{FlatSpec, ShouldMatchers} | |
import roger.AggregationOperation.AggregationOperation | |
case class Metric(id: String, aggregationOperation: AggregationOperation) | |
case class Dimension(id: String) | |
object AggregationOperation extends Enumeration { | |
type AggregationOperation = Value | |
val Sum, Average, Min, Max, Count = Value | |
} | |
/** | |
* Think of a RowSelection as a typed SQL table. We use this selection to | |
* represent OLAP cubes. | |
* | |
* Headers are the names of each column, with an additional information about | |
* either we are dealing with a dimension or a metric. | |
* | |
* Rows are double dimensions arrays. | |
* Each row is viewed as 2 concatenated sequence: one of strings for dimension values, the others of numerics. | |
* | |
* Ex: | |
* ["ga:origin", "ga:browser"] ["ga:visits", "ga:timeOnSite"] | |
* ["France", "Chrome"] [20.0, 345.5] | |
* | |
*/ | |
case class RowSelection( | |
metricHeaders: Seq[Metric], | |
dimensionHeaders: Seq[Dimension], | |
metricRows: Seq[IndexedSeq[Double]], | |
dimensionRows: Seq[IndexedSeq[String]]) { | |
def take(n: Int): RowSelection = { | |
/// To be implemented | |
??? | |
} | |
def ++(other: RowSelection): RowSelection = { | |
/// To be implemented | |
??? | |
} | |
def filter(col: Dimension, f: (String) => Boolean): RowSelection = { | |
/// To be implemented | |
??? | |
} | |
def groupByColumns(cols: Seq[Dimension]): RowSelection = { | |
///To be implemented | |
??? | |
} | |
} | |
class RowSelectionSpec extends FlatSpec with ShouldMatchers { | |
val metric1 = Metric("m1", AggregationOperation.Sum) | |
val metric2 = Metric("m2", AggregationOperation.Average) | |
val dimension1 = Dimension("d1") | |
val dimension2 = Dimension("d2") | |
val selection = RowSelection( | |
Seq(metric1, metric2), | |
Seq(dimension1, dimension2), | |
Seq(IndexedSeq(1.0, 3.0), IndexedSeq(2.0, 9.0)), | |
Seq(IndexedSeq("dimVal11", "dimVal12"), IndexedSeq("dimVal21", "dimVal22")) | |
) | |
"A RowSelection" should "take the n first rows" in { | |
val taken = selection.take(1) | |
taken.metricRows should have size 1 | |
taken.dimensionRows should have size 1 | |
} | |
it should "add a selection to another selection" in { | |
val other = selection | |
val added = selection ++ other | |
added.metricHeaders should equal(selection.metricHeaders) | |
added.dimensionHeaders should equal(selection.dimensionHeaders) | |
added.metricRows should equal(Seq(IndexedSeq(1.0, 3.0), IndexedSeq(2.0, 9.0), IndexedSeq(1.0, 3.0), IndexedSeq(2.0, 9.0))) | |
added.dimensionRows should equal(Seq(IndexedSeq("dimVal11", "dimVal12"), IndexedSeq("dimVal21", "dimVal22"), IndexedSeq("dimVal11", "dimVal12"), IndexedSeq("dimVal21", "dimVal22"))) | |
} | |
it should "filter the selection" in { | |
val f: (String => Boolean) = dimVal => dimVal == "dimVal11" | |
val filtered = selection.filter(dimension1, f) | |
filtered.metricRows should equal(Seq(IndexedSeq(1.0, 3.0))) | |
filtered.dimensionRows should equal(Seq(IndexedSeq("dimVal11", "dimVal12"))) | |
} | |
it should "group by columns" in { | |
val s = selection.copy(dimensionRows = Seq(IndexedSeq("dimVal1", "dimVal2"), IndexedSeq("dimVal1", "dimVal2"))) | |
val grouped = s.groupByColumns(Seq(dimension1, dimension2)) | |
grouped.dimensionRows should equal(Seq(IndexedSeq("dimVal1", "dimVal2"))) | |
grouped.metricRows should equal(Seq(IndexedSeq(3.0, 6.0))) | |
} | |
} |
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