feat(workflow-operator): compare Filter's exported predicates the way the engine does

common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/filter/SpecializedFilterOpDesc.scala

@@ -21,13 +21,16 @@ package org.apache.texera.amber.operator.filter
 
 import com.fasterxml.jackson.annotation.{JsonProperty, JsonPropertyDescription}
 import org.apache.texera.amber.core.executor.OpExecWithClassName
+import org.apache.texera.amber.core.tuple.{AttributeType, Schema}
 import org.apache.texera.amber.core.virtualidentity.{ExecutionIdentity, WorkflowIdentity}
-import org.apache.texera.amber.core.workflow.{InputPort, OutputPort, PhysicalOp}
-import org.apache.texera.amber.operator.StandaloneCodeGenerator
+import org.apache.texera.amber.core.workflow.{InputPort, OutputPort, PhysicalOp, PortIdentity}
+import org.apache.texera.amber.operator.{StandaloneCodeGenerator, StandaloneHelpers}
 import org.apache.texera.amber.operator.metadata.{OperatorGroupConstants, OperatorInfo}
 import org.apache.texera.amber.pybuilder.PythonTemplateBuilder.pyStringLiteral
 import org.apache.texera.amber.util.JSONUtils.objectMapper
 
+import scala.util.Try
+
 class SpecializedFilterOpDesc extends FilterOpDesc with StandaloneCodeGenerator {
 
   @JsonProperty(value = "predicates", required = true)
@@ -63,42 +66,167 @@ class SpecializedFilterOpDesc extends FilterOpDesc with StandaloneCodeGenerator
     )
   }
 
-  override def generateStandaloneCode(): String = {
+  override def generateStandaloneCode(): String = generateStandaloneCode(Map.empty)
+
+  override def generateStandaloneCode(inputSchemas: Map[PortIdentity, Schema]): String = {
     // No predicate keeps no row: the executor's filter is `predicates.exists`,
     // which answers false on an empty list. Passing the frame through would be
     // the opposite answer.
     if (predicates.isEmpty) return "out1df = in1df.iloc[0:0].copy()"
+    val schema = inputSchemas.values.headOption
     val conditions = predicates.map { p =>
       val colLit = pyStringLiteral(p.attribute)
       p.condition match {
         case ComparisonType.IS_NULL     => s"""(in1df[$colLit].isna())"""
         case ComparisonType.IS_NOT_NULL => s"""(in1df[$colLit].notna())"""
-        case other =>
-          val op = other.getName // returns "=", ">=", "<", etc. (see ComparisonType.java)
-          val pyOp = if (op == "=") "==" else op
-          // notna mirrors FilterPredicate, which answers false for every condition
-          // but IS_NULL / IS_NOT_NULL once the field is null. Only `!=` needs it —
-          // pandas answers True there, where every other operator answers False —
-          // but guarding all of them keeps the one rule visible in one place.
-          s"""(in1df[$colLit].notna() & (in1df[$colLit] $pyOp ${coerceValue(p.value)}))"""
+        case other                      =>
+          // FilterPredicate finds the field through Schema, which ignores case,
+          // and compares by the type declared there. Without a schema the
+          // column's dtype stands in for its type.
+          val keep = schema
+            .flatMap(s => Try(s.getAttribute(p.attribute)).toOption)
+            .map(a => SpecializedFilterOpDesc.keepFor(a.getType))
+            .getOrElse("_texera_filter_keep")
+          val opLit = pyStringLiteral(other.getName)
+          val valueLit = pyStringLiteral(Option(p.value).getOrElse(""))
+          s"$keep(in1df[$colLit], $opLit, $valueLit)"
       }
     }
     s"out1df = in1df[${conditions.mkString(" | ")}].reset_index(drop=True)"
   }
 
-  // Try numeric coercion so generated code compares column values against the right type.
-  // Strings that don't parse fall through to a quoted string literal.
-  private def coerceValue(raw: String): String = {
-    try {
-      raw.toInt.toString
-    } catch {
-      case _: NumberFormatException =>
-        try {
-          raw.toDouble.toString
-        } catch {
-          case _: NumberFormatException =>
-            pyStringLiteral(raw)
-        }
+  override def standaloneHelpers(): Seq[String] =
+    Seq(StandaloneHelpers.AttributeCasts, SpecializedFilterOpDesc.FilterPredicates)
+}
+
+object SpecializedFilterOpDesc {
+
+  /** The function that compares a column of `attributeType`, so a script calls only the one
+    * its column needs.
+    */
+  def keepFor(attributeType: AttributeType): String =
+    attributeType match {
+      case AttributeType.INTEGER | AttributeType.DOUBLE => "_texera_filter_keep_double"
+      case AttributeType.LONG                           => "_texera_filter_keep_long"
+      case AttributeType.BOOLEAN                        => "_texera_filter_keep_boolean"
+      case AttributeType.TIMESTAMP                      => "_texera_filter_keep_timestamp"
+      case _                                            => "_texera_filter_keep_string"
     }
-  }
+
+  /** `FilterPredicate.evaluate`, one function per type the engine compares apart. A null passes
+    * nothing.
+    *
+    *  - `_texera_filter_keep_double`: INTEGER and DOUBLE by `Double.compareTo`, NaN above all.
+    *  - `_texera_filter_keep_long`: LONG, the value read by `Long.valueOf`.
+    *  - `_texera_filter_keep_boolean`: BOOLEAN as lower-case text.
+    *  - `_texera_filter_keep_timestamp`: TIMESTAMP by whole milliseconds in the machine's zone.
+    *  - `_texera_filter_keep_string`: STRING as numbers when both parse, else by UTF-16 units.
+    *  - `_texera_filter_keep`: the type read off the column's dtype, when no schema says it.
+    *
+    * The value is read with `_texera_java_trim`, `_texera_java_double` and `_texera_parse_int`,
+    * and a double is ordered by `_texera_double_key`, all from
+    * [[StandaloneHelpers.AttributeCasts]].
+    */
+  val FilterPredicates: String =
+    """def _texera_filter_text_key(s):
+      |    return s.encode("utf-16-be", "surrogatepass")
+      |
+      |
+      |def _texera_filter_compared(left, right):
+      |    return (left > right) - (left < right)
+      |
+      |
+      |def _texera_filter_rows(column, condition, order):
+      |    passes = {
+      |        "=": lambda c: c == 0,
+      |        ">": lambda c: c > 0,
+      |        ">=": lambda c: c >= 0,
+      |        "<": lambda c: c < 0,
+      |        "<=": lambda c: c <= 0,
+      |        "!=": lambda c: c != 0,
+      |    }[condition]
+      |    return pd.Series(
+      |        [
+      |            False if missing else passes(order(v))
+      |            for v, missing in zip(column, column.isna())
+      |        ],
+      |        index=column.index,
+      |        dtype=bool,
+      |    )
+      |
+      |
+      |def _texera_filter_keep_double(column, condition, value):
+      |    target = _texera_double_key(_texera_java_double(value))
+      |
+      |    def order(v):
+      |        return _texera_filter_compared(_texera_double_key(float(v)), target)
+      |
+      |    return _texera_filter_rows(column, condition, order)
+      |
+      |
+      |def _texera_filter_keep_long(column, condition, value):
+      |    target = _texera_parse_int(value, 64)
+      |
+      |    def order(v):
+      |        return _texera_filter_compared(int(v), target)
+      |
+      |    return _texera_filter_rows(column, condition, order)
+      |
+      |
+      |def _texera_filter_keep_boolean(column, condition, value):
+      |    target = _texera_filter_text_key(_texera_java_trim(value).lower())
+      |
+      |    def order(v):
+      |        return _texera_filter_compared(_texera_filter_text_key("true" if v else "false"), target)
+      |
+      |    return _texera_filter_rows(column, condition, order)
+      |
+      |
+      |def _texera_filter_keep_timestamp(column, condition, value):
+      |    zone = _texera_local_zone()
+      |
+      |    def wall_clock(ts):
+      |        ts = pd.Timestamp(ts).floor("ms")
+      |        if ts.tzinfo is None:
+      |            return ts
+      |        return pd.Timestamp(_texera_local_wall_clock(ts.to_pydatetime(), zone))
+      |
+      |    target = wall_clock(_texera_java_trim(value))
+      |
+      |    def order(v):
+      |        return _texera_filter_compared(wall_clock(v), target)
+      |
+      |    return _texera_filter_rows(column, condition, order)
+      |
+      |
+      |def _texera_filter_keep_string(column, condition, value):
+      |    try:
+      |        value_number = _texera_double_key(_texera_java_double(value))
+      |    except ValueError:
+      |        value_number = None
+      |
+      |    def order(v):
+      |        text = str(v)
+      |        if value_number is not None:
+      |            try:
+      |                number = _texera_double_key(_texera_java_double(text))
+      |                return _texera_filter_compared(number, value_number)
+      |            except ValueError:
+      |                pass
+      |        return _texera_filter_compared(
+      |            _texera_filter_text_key(text), _texera_filter_text_key(value)
+      |        )
+      |
+      |    return _texera_filter_rows(column, condition, order)
+      |
+      |
+      |def _texera_filter_keep(column, condition, value):
+      |    dtype = column.dtype
+      |    if pd.api.types.is_bool_dtype(dtype):
+      |        return _texera_filter_keep_boolean(column, condition, value)
+      |    if pd.api.types.is_integer_dtype(dtype) or pd.api.types.is_float_dtype(dtype):
+      |        return _texera_filter_keep_double(column, condition, value)
+      |    if pd.api.types.is_datetime64_any_dtype(dtype):
+      |        return _texera_filter_keep_timestamp(column, condition, value)
+      |    return _texera_filter_keep_string(column, condition, value)""".stripMargin
 }