Remove incorrect Expression and SQL registry

Signed-off-by: Jason T. Brown <jason@astraea.earth>

Author: vpipkt

core/src/main/scala/org/locationtech/rasterframes/expressions/aggregates/ApproxCellQuantilesAggregate.scala

@@ -23,10 +23,7 @@ package org.locationtech.rasterframes.expressions.aggregates
 
 import geotrellis.raster.{Tile, isNoData}
 import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder
-import org.apache.spark.sql.catalyst.expressions.aggregate.{AggregateExpression, AggregateFunction, AggregateMode, Complete}
-import org.apache.spark.sql.catalyst.expressions.{ExprId, Expression, ExpressionDescription, NamedExpression}
 import org.apache.spark.sql.catalyst.util.QuantileSummaries
-import org.apache.spark.sql.execution.aggregate.ScalaUDAF
 import org.apache.spark.sql.expressions.{MutableAggregationBuffer, UserDefinedAggregateFunction}
 import org.apache.spark.sql.{Column, Encoder, Row, TypedColumn, types}
 import org.apache.spark.sql.types.{DataTypes, StructField, StructType}
@@ -88,29 +85,4 @@ object ApproxCellQuantilesAggregate {
       .as(s"rf_agg_approx_quantiles")
       .as[Seq[Double]]
   }
-
-  /** Adapter hack to allow UserDefinedAggregateFunction to be referenced as an expression. */
-  @ExpressionDescription(
-    usage = "_FUNC_(tile, probabilities, relativeError) - Compute aggregate cell histogram over a tile column.",
-    arguments = """
-  Arguments:
-    * tile - tile column to analyze
-    * probabilities - array of double values in [0, 1] at which to compute quantiles
-    * relativeError - non-negative error tolerance""",
-    examples = """
-  Examples:
-    > SELECT _FUNC_(tile, array(0.1, 0.25, 0.5, 0.75, 0.9), 0.001);
-      ..."""
-  )
-  class ApproxCellQuantilesUDAF(aggregateFunction: AggregateFunction, mode: AggregateMode, isDistinct: Boolean, resultId: ExprId)
-    extends AggregateExpression(aggregateFunction, mode, isDistinct, resultId) {
-    def this(child: Expression, probabilities: Seq[Double], relativeError: Double) =
-      this(ScalaUDAF(Seq(ExtractTile(child)), new ApproxCellQuantilesAggregate(probabilities, relativeError)), Complete, false, NamedExpression.newExprId)
-    override def nodeName: String = "rf_agg_approx_quantiles"
-  }
-
-  object ApproxCellQuantilesUDAF {
-    def apply(child: Expression, probabilities: Seq[Double], relativeError: Double): ApproxCellQuantilesUDAF = new ApproxCellQuantilesUDAF(child, probabilities, relativeError)
-    def apply(child: Expression, probabilities: Seq[Double]): ApproxCellQuantilesUDAF = new ApproxCellQuantilesUDAF(child, probabilities, 0.00001)
-  }
 }

core/src/main/scala/org/locationtech/rasterframes/expressions/package.scala

@@ -117,7 +117,6 @@ package object expressions {
     registry.registerExpression[CellCountAggregate.NoDataCells]("rf_agg_no_data_cells")
     registry.registerExpression[CellStatsAggregate.CellStatsAggregateUDAF]("rf_agg_stats")
     registry.registerExpression[HistogramAggregate.HistogramAggregateUDAF]("rf_agg_approx_histogram")
-    registry.registerExpression[ApproxCellQuantilesAggregate.ApproxCellQuantilesUDAF]("rf_agg_approx_quantiles")
     registry.registerExpression[LocalStatsAggregate.LocalStatsAggregateUDAF]("rf_agg_local_stats")
     registry.registerExpression[LocalTileOpAggregate.LocalMinUDAF]("rf_agg_local_min")
     registry.registerExpression[LocalTileOpAggregate.LocalMaxUDAF]("rf_agg_local_max")

core/src/test/scala/org/locationtech/rasterframes/RasterFramesStatsSpec.scala

@@ -72,16 +72,6 @@ class RasterFramesStatsSpec extends TestEnvironment with TestData {
       result should contain inOrderOnly(7963.0, 10068.0, 12160.0)
     }
 
-    it("should compute approx percentiles with SQL") {
-      val result = df.selectExpr("rf_agg_approx_quantiles(tile, array(0.1, 0.5, 0.9), 0.00001) as iles")
-        .first()
-        .getSeq[Double](0)
-
-      result.length should be (3)
-
-      // computing externally with numpy we arrive at 7963, 10068, 12160 for these quantiles
-      result should contain inOrderOnly(7963.0, 10068.0, 12160.0)
-    }
   }
 }
 

docs/src/main/paradox/reference.md

@@ -632,6 +632,8 @@ Aggregates over all of the rows in DataFrame of `tile` and returns a count of ea
 
     Array[Double] rf_agg_approx_quantiles(Tile tile, List[float] probabilities, float relative_error)
 
+__Not supported in SQL.__
+    
 Calculates the approximate quantiles of a tile column of a DataFrame. `probabilities` is a list of float values at which to compute the quantiles. These must belong to [0, 1]. For example 0 is the minimum, 0.5 is the median, 1 is the maximum. Returns an array of values approximately at the specified `probabilities`.
 
 ## Tile Local Aggregate Statistics