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/*
 * Licensed to Metamarkets Group Inc. (Metamarkets) under one
 * or more contributor license agreements. See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership. Metamarkets licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License. You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied. See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */

package io.druid.query.aggregation.histogram.sql;

import com.google.common.collect.ImmutableList;
import io.druid.java.util.common.StringUtils;
import io.druid.query.aggregation.AggregatorFactory;
import io.druid.query.aggregation.histogram.ApproximateHistogram;
import io.druid.query.aggregation.histogram.ApproximateHistogramAggregatorFactory;
import io.druid.query.aggregation.histogram.ApproximateHistogramFoldingAggregatorFactory;
import io.druid.query.aggregation.histogram.QuantilePostAggregator;
import io.druid.segment.VirtualColumn;
import io.druid.segment.column.ValueType;
import io.druid.segment.virtual.ExpressionVirtualColumn;
import io.druid.sql.calcite.aggregation.Aggregation;
import io.druid.sql.calcite.aggregation.SqlAggregator;
import io.druid.sql.calcite.expression.DruidExpression;
import io.druid.sql.calcite.expression.Expressions;
import io.druid.sql.calcite.planner.PlannerContext;
import io.druid.sql.calcite.table.RowSignature;
import org.apache.calcite.rel.core.AggregateCall;
import org.apache.calcite.rel.core.Project;
import org.apache.calcite.rex.RexBuilder;
import org.apache.calcite.rex.RexLiteral;
import org.apache.calcite.rex.RexNode;
import org.apache.calcite.sql.SqlAggFunction;
import org.apache.calcite.sql.SqlFunctionCategory;
import org.apache.calcite.sql.SqlKind;
import org.apache.calcite.sql.type.OperandTypes;
import org.apache.calcite.sql.type.ReturnTypes;
import org.apache.calcite.sql.type.SqlTypeFamily;
import org.apache.calcite.sql.type.SqlTypeName;

import javax.annotation.Nullable;
import java.util.ArrayList;
import java.util.List;

public class QuantileSqlAggregator implements SqlAggregator
{
  private static final SqlAggFunction FUNCTION_INSTANCE = new QuantileSqlAggFunction();
  private static final String NAME = "APPROX_QUANTILE";

  @Override
  public SqlAggFunction calciteFunction()
  {
    return FUNCTION_INSTANCE;
  }

  @Nullable
  @Override
  public Aggregation toDruidAggregation(
      final PlannerContext plannerContext,
      final RowSignature rowSignature,
      final RexBuilder rexBuilder,
      final String name,
      final AggregateCall aggregateCall,
      final Project project,
      final List existingAggregations,
      final boolean finalizeAggregations
  )
  {
    final DruidExpression input = Expressions.toDruidExpression(
        plannerContext,
        rowSignature,
        Expressions.fromFieldAccess(
            rowSignature,
            project,
            aggregateCall.getArgList().get(0)
        )
    );
    if (input == null) {
      return null;
    }

    final AggregatorFactory aggregatorFactory;
    final String histogramName = StringUtils.format("%s:agg", name);
    final RexNode probabilityArg = Expressions.fromFieldAccess(
        rowSignature,
        project,
        aggregateCall.getArgList().get(1)
    );

    if (!probabilityArg.isA(SqlKind.LITERAL)) {
      // Probability must be a literal in order to plan.
      return null;
    }

    final float probability = ((Number) RexLiteral.value(probabilityArg)).floatValue();
    final int resolution;

    if (aggregateCall.getArgList().size() >= 3) {
      final RexNode resolutionArg = Expressions.fromFieldAccess(
          rowSignature,
          project,
          aggregateCall.getArgList().get(2)
      );

      if (!resolutionArg.isA(SqlKind.LITERAL)) {
        // Resolution must be a literal in order to plan.
        return null;
      }

      resolution = ((Number) RexLiteral.value(resolutionArg)).intValue();
    } else {
      resolution = ApproximateHistogram.DEFAULT_HISTOGRAM_SIZE;
    }

    final int numBuckets = ApproximateHistogram.DEFAULT_BUCKET_SIZE;
    final float lowerLimit = Float.NEGATIVE_INFINITY;
    final float upperLimit = Float.POSITIVE_INFINITY;

    // Look for existing matching aggregatorFactory.
    for (final Aggregation existing : existingAggregations) {
      for (AggregatorFactory factory : existing.getAggregatorFactories()) {
        if (factory instanceof ApproximateHistogramAggregatorFactory) {
          final ApproximateHistogramAggregatorFactory theFactory = (ApproximateHistogramAggregatorFactory) factory;

          // Check input for equivalence.
          final boolean inputMatches;
          final VirtualColumn virtualInput = existing.getVirtualColumns()
                                                     .stream()
                                                     .filter(
                                                         virtualColumn ->
                                                             virtualColumn.getOutputName()
                                                                          .equals(theFactory.getFieldName())
                                                     )
                                                     .findFirst()
                                                     .orElse(null);

          if (virtualInput == null) {
            inputMatches = input.isDirectColumnAccess()
                           && input.getDirectColumn().equals(theFactory.getFieldName());
          } else {
            inputMatches = ((ExpressionVirtualColumn) virtualInput).getExpression()
                                                                   .equals(input.getExpression());
          }

          final boolean matches = inputMatches
                                  && theFactory.getResolution() == resolution
                                  && theFactory.getNumBuckets() == numBuckets
                                  && theFactory.getLowerLimit() == lowerLimit
                                  && theFactory.getUpperLimit() == upperLimit;

          if (matches) {
            // Found existing one. Use this.
            return Aggregation.create(
                ImmutableList.of(),
                new QuantilePostAggregator(name, factory.getName(), probability)
            );
          }
        }
      }
    }

    // No existing match found. Create a new one.
    final List virtualColumns = new ArrayList<>();

    if (input.isDirectColumnAccess()) {
      if (rowSignature.getColumnType(input.getDirectColumn()) == ValueType.COMPLEX) {
        aggregatorFactory = new ApproximateHistogramFoldingAggregatorFactory(
            histogramName,
            input.getDirectColumn(),
            resolution,
            numBuckets,
            lowerLimit,
            upperLimit
        );
      } else {
        aggregatorFactory = new ApproximateHistogramAggregatorFactory(
            histogramName,
            input.getDirectColumn(),
            resolution,
            numBuckets,
            lowerLimit,
            upperLimit
        );
      }
    } else {
      final ExpressionVirtualColumn virtualColumn = input.toVirtualColumn(
          StringUtils.format("%s:v", name),
          ValueType.FLOAT,
          plannerContext.getExprMacroTable()
      );
      virtualColumns.add(virtualColumn);
      aggregatorFactory = new ApproximateHistogramAggregatorFactory(
          histogramName,
          virtualColumn.getOutputName(),
          resolution,
          numBuckets,
          lowerLimit,
          upperLimit
      );
    }

    return Aggregation.create(
        virtualColumns,
        ImmutableList.of(aggregatorFactory),
        new QuantilePostAggregator(name, histogramName, probability)
    );
  }

  private static class QuantileSqlAggFunction extends SqlAggFunction
  {
    private static final String SIGNATURE1 = "'" + NAME + "(column, probability)'\n";
    private static final String SIGNATURE2 = "'" + NAME + "(column, probability, resolution)'\n";

    QuantileSqlAggFunction()
    {
      super(
          NAME,
          null,
          SqlKind.OTHER_FUNCTION,
          ReturnTypes.explicit(SqlTypeName.DOUBLE),
          null,
          OperandTypes.or(
              OperandTypes.and(
                  OperandTypes.sequence(SIGNATURE1, OperandTypes.ANY, OperandTypes.LITERAL),
                  OperandTypes.family(SqlTypeFamily.ANY, SqlTypeFamily.NUMERIC)
              ),
              OperandTypes.and(
                  OperandTypes.sequence(SIGNATURE2, OperandTypes.ANY, OperandTypes.LITERAL, OperandTypes.LITERAL),
                  OperandTypes.family(SqlTypeFamily.ANY, SqlTypeFamily.NUMERIC, SqlTypeFamily.EXACT_NUMERIC)
              )
          ),
          SqlFunctionCategory.NUMERIC,
          false,
          false
      );
    }
  }
}