/**
 * 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.drill.exec.store.parquet.columnreaders;

import org.apache.drill.BaseTestQuery;
import org.apache.drill.exec.planner.physical.PlannerSettings;
import org.junit.AfterClass;
import org.junit.BeforeClass;
import org.junit.Test;

public class TestColumnReaderFactory extends BaseTestQuery {
  // enable decimal data type
  @BeforeClass
  public static void enableDecimalDataType() throws Exception {
    test(String.format("alter session set `%s` = true", PlannerSettings.ENABLE_DECIMAL_DATA_TYPE_KEY));
  }

  @AfterClass
  public static void disableDecimalDataType() throws Exception {
    test(String.format("alter session set `%s` = false", PlannerSettings.ENABLE_DECIMAL_DATA_TYPE_KEY));
  }

  /**
   * check if Time and TimeStamp are read correctly with dictionary encoding.
   */
  @Test
  public void testTimeAndTimeStampWithDictionary() throws Exception {
    // the file 'time_dictionary.parquet' uses a PLAIN_DICTIONARY encoding and contains 4 columns:
    // time_opt: INT32/TIME_MILLIS/OPTIONAL
    // time_req: INT32/TIME_MILLIS/REQUIRED
    // timestampt_opt: INT64/TIMESTAMP_MILLIS/OPTIONAL
    // timestampt_req: INT64/TIMESTAMP_MILLIS/REQUIRED

    // query parquet file. We shouldn't get any exception
    testNoResult("SELECT * FROM cp.`parquet/time_dictionary.parquet`");
  }

  /**
   * check if Time and TimeStamp are read correctly with plain encoding.
   */
  @Test
  public void testTimeAndTimeStampWithNoDictionary() throws Exception {
    // the file 'time_dictionary.parquet' uses a PLAIN encoding and contains 4 columns:
    // time_opt: INT32/TIME_MILLIS/OPTIONAL
    // time_req: INT32/TIME_MILLIS/REQUIRED
    // timestampt_opt: INT64/TIMESTAMP_MILLIS/OPTIONAL
    // timestampt_req: INT64/TIMESTAMP_MILLIS/REQUIRED

    // query parquet file. We shouldn't get any exception
    testNoResult("SELECT * FROM cp.`parquet/time_nodictionary.parquet`");
  }

  /**
   * check if Decimal9 and Decimal18 are read correctly with dictionary encoding.
   */
  @Test
  public void testDecimal9AndDecimal18WithDictionary() throws Exception {
    // the file 'decimal_dictionary.parquet' uses a PLAIN_DICTIONARY encoding and contains 4 columns:
    // d9_opt: INT32/DECIMAL9/OPTIONAL
    // d9_req: INT32/DECIMAL9/REQUIRED
    // d18_opt: INT64/DECIMAL18/OPTIONAL
    // d18_req: INT64/DECIMAL18/REQUIRED

    // query parquet file. We shouldn't get any exception
    testNoResult("SELECT * FROM cp.`parquet/decimal_dictionary.parquet`");
  }

  /**
   * check if Decimal9 and Decimal18 are read correctly with plain encoding.
   */
  @Test
  public void testDecimal9AndDecimal18WithNoDictionary() throws Exception {
    // the file 'decimal_dictionary.parquet' uses a PLAIN encoding and contains 4 columns:
    // d9_opt: INT32/DECIMAL9/OPTIONAL
    // d9_req: INT32/DECIMAL9/REQUIRED
    // d18_opt: INT64/DECIMAL18/OPTIONAL
    // d18_req: INT64/DECIMAL18/REQUIRED

    // query parquet file. We shouldn't get any exception
    testNoResult("SELECT * FROM cp.`parquet/decimal_nodictionary.parquet`");
  }

  /**
   * check if BigInt is read correctly with dictionary encoding.
   */
  @Test
  public void testBigIntWithDictionary() throws Exception {
    String query = "select sum(ts) as total from cp.`parquet/bigIntDictionary.parquet`";

    testBuilder()
    .sqlQuery(query)
    .ordered()
    .baselineColumns("total")
    .baselineValues(190928593476806865L)
    .build().run();
  }
}