Sample.java

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF 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 org.apache.calcite.rel.core;

import org.apache.calcite.plan.Convention;
import org.apache.calcite.plan.RelOptCluster;
import org.apache.calcite.plan.RelOptSamplingParameters;
import org.apache.calcite.plan.RelTraitSet;
import org.apache.calcite.rel.RelInput;
import org.apache.calcite.rel.RelNode;
import org.apache.calcite.rel.RelWriter;
import org.apache.calcite.rel.SingleRel;

import java.math.BigDecimal;
import java.util.List;

/**
 * Relational expression that returns a sample of the rows from its input.
 *
 * <p>In SQL, a sample is expressed using the {@code TABLESAMPLE BERNOULLI} or
 * {@code SYSTEM} keyword applied to a table, view or sub-query.
 */
public class Sample extends SingleRel {
  //~ Instance fields --------------------------------------------------------

  private final RelOptSamplingParameters params;

  //~ Constructors -----------------------------------------------------------

  public Sample(RelOptCluster cluster, RelNode child,
      RelOptSamplingParameters params) {
    super(cluster, cluster.traitSetOf(Convention.NONE), child);
    this.params = params;
  }

  /**
   * Creates a Sample by parsing serialized output.
   */
  public Sample(RelInput input) {
    this(input.getCluster(), input.getInput(), getSamplingParameters(input));
  }

  //~ Methods ----------------------------------------------------------------

  private static RelOptSamplingParameters getSamplingParameters(
      RelInput input) {
    String mode = input.getString("mode");
    final boolean bernoulli = "bernoulli".equals(mode);
    final BigDecimal rate = input.getBigDecimal("rate");
    final Object repeatableSeed = input.get("repeatableSeed");
    final int seed;
    final boolean repeatable;
    if (repeatableSeed instanceof Number) {
      repeatable = true;
      seed = ((Number) repeatableSeed).intValue();
    } else {
      repeatable = false;
      seed = 0;
    }
    return new RelOptSamplingParameters(bernoulli, rate, repeatable, seed);
  }

  @Override public RelNode copy(RelTraitSet traitSet, List<RelNode> inputs) {
    assert traitSet.containsIfApplicable(Convention.NONE);
    return new Sample(getCluster(), sole(inputs), params);
  }

  /**
   * Retrieve the sampling parameters for this Sample.
   */
  public RelOptSamplingParameters getSamplingParameters() {
    return params;
  }

  @Override public RelWriter explainTerms(RelWriter pw) {
    return super.explainTerms(pw)
        .item("mode", params.isBernoulli() ? "bernoulli" : "system")
        .item("rate", params.sampleRate)
        .item("repeatableSeed",
            params.isRepeatable() ? params.getRepeatableSeed() : "-");
  }
}