/*
 * 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.beam.sdk.extensions.sql;

import static com.google.common.base.Preconditions.checkArgument;
import static java.util.stream.Collectors.toList;
import static org.apache.beam.sdk.schemas.Schema.toSchema;
import static org.apache.beam.sdk.values.Row.toRow;

import com.google.common.collect.Lists;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.stream.Stream;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.schemas.Schema;
import org.apache.beam.sdk.schemas.Schema.FieldType;
import org.apache.beam.sdk.testing.TestStream;
import org.apache.beam.sdk.transforms.DoFn;
import org.apache.beam.sdk.transforms.SerializableFunctions;
import org.apache.beam.sdk.values.PBegin;
import org.apache.beam.sdk.values.PCollection;
import org.apache.beam.sdk.values.PCollectionTuple;
import org.apache.beam.sdk.values.Row;
import org.apache.beam.sdk.values.TupleTag;
import org.joda.time.Instant;

/** Test utilities. */
public class TestUtils {
  /** A {@code DoFn} to convert a {@code BeamSqlRow} to a comparable {@code String}. */
  public static class BeamSqlRow2StringDoFn extends DoFn<Row, String> {
    @ProcessElement
    public void processElement(ProcessContext ctx) {
      ctx.output(ctx.element().toString());
    }
  }

  /** Convert list of {@code BeamSqlRow} to list of {@code String}. */
  public static List<String> beamSqlRows2Strings(List<Row> rows) {
    List<String> strs = new ArrayList<>();
    for (Row row : rows) {
      strs.add(row.toString());
    }

    return strs;
  }

  public static RowsBuilder rowsBuilderOf(Schema type) {
    return RowsBuilder.of(type);
  }

  /**
   * Convenient way to build a list of {@code BeamSqlRow}s.
   *
   * <p>You can use it like this:
   *
   * <pre>{@code
   * TestUtils.RowsBuilder.of(
   *   Types.INTEGER, "order_id",
   *   Types.INTEGER, "sum_site_id",
   *   Types.VARCHAR, "buyer"
   * ).addRows(
   *   1, 3, "james",
   *   2, 5, "bond"
   *   ).getStringRows()
   * }</pre>
   *
   * {@code}
   */
  public static class RowsBuilder {
    private Schema type;
    private List<Row> rows = new ArrayList<>();

    /**
     * Create a RowsBuilder with the specified row type info.
     *
     * <p>For example:
     *
     * <pre>{@code
     * TestUtils.RowsBuilder.of(
     *   Types.INTEGER, "order_id",
     *   Types.INTEGER, "sum_site_id",
     *   Types.VARCHAR, "buyer"
     * )
     * }</pre>
     *
     * @args pairs of column type and column names.
     */
    public static RowsBuilder of(final Object... args) {
      Schema beamSQLSchema = buildBeamSqlSchema(args);
      RowsBuilder builder = new RowsBuilder();
      builder.type = beamSQLSchema;

      return builder;
    }

    /**
     * Create a RowsBuilder with the specified row type info.
     *
     * <p>For example:
     *
     * <pre>{@code
     * TestUtils.RowsBuilder.of(
     *   schema
     * )
     * }</pre>
     */
    public static RowsBuilder of(final Schema schema) {
      RowsBuilder builder = new RowsBuilder();
      builder.type = schema;

      return builder;
    }

    /**
     * Add rows to the builder.
     *
     * <p>Note: check the class javadoc for for detailed example.
     */
    public RowsBuilder addRows(final Object... args) {
      this.rows.addAll(buildRows(type, Arrays.asList(args)));
      return this;
    }

    /**
     * Add rows to the builder.
     *
     * <p>Note: check the class javadoc for for detailed example.
     */
    public RowsBuilder addRows(final List args) {
      this.rows.addAll(buildRows(type, args));
      return this;
    }

    public List<Row> getRows() {
      return rows;
    }

    public List<String> getStringRows() {
      return beamSqlRows2Strings(rows);
    }

    public PCollectionBuilder getPCollectionBuilder() {
      return pCollectionBuilder().withSchema(type).withRows(rows);
    }
  }

  public static PCollectionBuilder pCollectionBuilder() {
    return new PCollectionBuilder();
  }

  static class PCollectionBuilder {
    private Schema type;
    private List<Row> rows;
    private String timestampField;
    private Pipeline pipeline;

    public PCollectionBuilder withSchema(Schema type) {
      this.type = type;
      return this;
    }

    public PCollectionBuilder withRows(List<Row> rows) {
      this.rows = rows;
      return this;
    }

    /** Event time field, defines watermark. */
    public PCollectionBuilder withTimestampField(String timestampField) {
      this.timestampField = timestampField;
      return this;
    }

    public PCollectionBuilder inPipeline(Pipeline pipeline) {
      this.pipeline = pipeline;
      return this;
    }

    /**
     * Builds an unbounded {@link PCollection} in {@link Pipeline} set by {@link
     * #inPipeline(Pipeline)}.
     *
     * <p>If timestamp field was set with {@link #withTimestampField(String)} then watermark will be
     * advanced to the values from that field.
     */
    public PCollection<Row> buildUnbounded() {
      checkArgument(pipeline != null);
      checkArgument(rows.size() > 0);

      if (type == null) {
        type = rows.get(0).getSchema();
      }

      TestStream.Builder<Row> values =
          TestStream.create(
              type, SerializableFunctions.identity(), SerializableFunctions.identity());

      for (Row row : rows) {
        if (timestampField != null) {
          values = values.advanceWatermarkTo(new Instant(row.getDateTime(timestampField)));
        }

        values = values.addElements(row);
      }

      return PBegin.in(pipeline).apply("unboundedPCollection", values.advanceWatermarkToInfinity());
    }
  }

  /**
   * Convenient way to build a {@link Schema}.
   *
   * <p>e.g.
   *
   * <pre>{@code
   * buildBeamSqlSchema(
   *     SqlCoders.BIGINT, "order_id",
   *     SqlCoders.INTEGER, "site_id",
   *     SqlCoders.DOUBLE, "price",
   *     SqlCoders.TIMESTAMP, "order_time"
   * )
   * }</pre>
   */
  public static Schema buildBeamSqlSchema(Object... args) {
    return Stream.iterate(0, i -> i + 2)
        .limit(args.length / 2)
        .map(i -> toRecordField(args, i))
        .collect(toSchema());
  }

  // TODO: support nested.
  private static Schema.Field toRecordField(Object[] args, int i) {
    return Schema.Field.of((String) args[i + 1], (FieldType) args[i]);
  }

  /**
   * Convenient way to build a {@code BeamSqlRow}s.
   *
   * <p>e.g.
   *
   * <pre>{@code
   * buildRows(
   *     schema,
   *     1, 1, 1, // the first row
   *     2, 2, 2, // the second row
   *     ...
   * )
   * }</pre>
   */
  public static List<Row> buildRows(Schema type, List<?> rowsValues) {
    return Lists.partition(rowsValues, type.getFieldCount())
        .stream()
        .map(values -> values.stream().collect(toRow(type)))
        .collect(toList());
  }

  public static <T> PCollectionTuple tuple(String tag, PCollection<T> pCollection) {

    return PCollectionTuple.of(new TupleTag<>(tag), pCollection);
  }

  public static <T, V> PCollectionTuple tuple(
      String tag1, PCollection<T> pCollection1, String tag2, PCollection<V> pCollection2) {

    return tuple(tag1, pCollection1).and(new TupleTag<>(tag2), pCollection2);
  }

  public static <T, V, W> PCollectionTuple tuple(
      String tag1,
      PCollection<T> pCollection1,
      String tag2,
      PCollection<V> pCollection2,
      String tag3,
      PCollection<W> pCollection3) {

    return tuple(
            tag1, pCollection1,
            tag2, pCollection2)
        .and(new TupleTag<>(tag3), pCollection3);
  }
}
