[Coral-Incremental] Cost calculation for RelNode

coral-incremental/src/main/java/com/linkedin/coral/incremental/RelNodeCostEstimator.java

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+/**
+ * Copyright 2024 LinkedIn Corporation. All rights reserved.
+ * Licensed under the BSD-2 Clause license.
+ * See LICENSE in the project root for license information.
+ */
+package com.linkedin.coral.incremental;
+
+import java.io.IOException;
+import java.nio.file.Files;
+import java.nio.file.Paths;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+
+import com.google.gson.JsonElement;
+import com.google.gson.JsonObject;
+import com.google.gson.JsonParser;
+
+import org.apache.calcite.plan.RelOptTable;
+import org.apache.calcite.rel.RelNode;
+import org.apache.calcite.rel.core.TableScan;
+import org.apache.calcite.rel.logical.LogicalJoin;
+import org.apache.calcite.rel.logical.LogicalProject;
+import org.apache.calcite.rel.logical.LogicalUnion;
+import org.apache.calcite.rel.type.RelDataType;
+import org.apache.calcite.rel.type.RelDataTypeField;
+import org.apache.calcite.rex.RexCall;
+import org.apache.calcite.rex.RexInputRef;
+import org.apache.calcite.rex.RexNode;
+
+import static java.lang.Math.*;
+
+
+/**
+ * RelNodeCostEstimator is a utility class designed to estimate the cost of executing relational operations
+ * in a query plan. It uses statistical information about table row counts and column distinct values
+ * to compute costs associated with different types of relational operations like table scans, joins,
+ * unions, and projections.
+ *
+ * <p>This class supports loading statistics from a JSON configuration file.
+ * For a relational operations (RelNode), the execution cost and row count are estimated based on
+ * these statistics and the input relational expressions.
+ *
+ * <p>The cost estimation takes into account factors such as I/O costs and data shuffling costs.
+ * The cost of writing a row to disk is IOCostValue, and the cost of shuffling a row
+ * between nodes is shuffleCostValue.
+ *
+ * <p>Cost is get from 'getCost' method, which returns the total cost of the query plan, and cost consists of
+ * execution cost and I/O cost.
+ */
+public class RelNodeCostEstimator {
+
+  class CostInfo {
+    // TODO: we may also need to add TableName field.
+    Double shuffleCost;
+    Double rowCount;
+
+    public CostInfo(Double shuffleCost, Double row) {
+      this.shuffleCost = shuffleCost;
+      this.rowCount = row;
+    }
+  }
+
+  class TableStatistic {
+    // The number of rows in the table
+    Double rowCount;
+    // The number of distinct values in each column
+    Map<String, Double> distinctCountByRow;
+  }
+
+  class JoinKey {
+    String leftTableName;
+    String rightTableName;
+    String leftFieldName;
+    String rightFieldName;
+
+    public JoinKey(String leftTableName, String rightTableName, String leftFieldName, String rightFieldName) {
+      this.leftTableName = leftTableName;
+      this.rightTableName = rightTableName;
+      this.leftFieldName = leftFieldName;
+      this.rightFieldName = rightFieldName;
+    }
+  }
+
+  private Map<String, TableStatistic> costStatistic = new HashMap<>();
+
+  private final Double IOCostValue;
+
+  private final Double shuffleCostValue;
+
+  public RelNodeCostEstimator(Double IOCostValue, Double shuffleCostValue) {
+    this.IOCostValue = IOCostValue;
+    this.shuffleCostValue = shuffleCostValue;
+  }
+
+  /**
+   * Loads statistics from a JSON configuration file and stores them in internal data structures.
+   *
+   * <p>This method reads a JSON file from the specified path, parses its content, and extracts
+   * statistical information. For each table in the JSON object, it retrieves the row count and
+   * distinct counts for each column. These values are then stored in the `stat` and `distinctStat`
+   * maps, respectively.
+   *
+   * @param configPath the path to the JSON configuration file
+   */
+  public void loadStatistic(String configPath) throws IOException {
+    try {
+      String content = new String(Files.readAllBytes(Paths.get(configPath)));
+      JsonObject jsonObject = new JsonParser().parse(content).getAsJsonObject();
+      for (Map.Entry<String, JsonElement> entry : jsonObject.entrySet()) {
+        TableStatistic tableStatistic = new TableStatistic();
+        String tableName = entry.getKey();
+        JsonObject tableObject = entry.getValue().getAsJsonObject();
+
+        Double rowCount = tableObject.get("RowCount").getAsDouble();
+
+        JsonObject distinctCounts = tableObject.getAsJsonObject("DistinctCounts");
+
+        tableStatistic.rowCount = rowCount;
+
+        for (Map.Entry<String, JsonElement> distinctEntry : distinctCounts.entrySet()) {
+          String columnName = distinctEntry.getKey();
+          Double distinctCount = distinctEntry.getValue().getAsDouble();
+
+          tableStatistic.distinctCountByRow.put(columnName, distinctCount);
+        }
+        costStatistic.put(tableName, tableStatistic);
+
+      }
+    } catch (IOException e) {
+      throw new IOException("Failed to load statistics from the configuration file: " + configPath, e);
+    }
+
+  }
+
+  /**
+   * Returns the total cost of executing a relational operation.
+   *
+   * <p>This method computes the cost of executing a relational operation based on the input
+   * relational expression. The cost is calculated as the sum of the execution cost and the I/O cost.
+   * We assume that I/O only occurs at the root of the query plan (Project) where we write the output to disk.
+   * So the cost is the sum of the shuffle cost of all children RelNodes and IOCostValue * row count of the root Project RelNode.
+   *
+   * @param rel the input relational expression
+   * @return the total cost of executing the relational operation
+   */
+  public Double getCost(RelNode rel) {
+    CostInfo executionCostInfo = getExecutionCost(rel);
+    Double IOCost = executionCostInfo.rowCount * IOCostValue;
+    return executionCostInfo.shuffleCost * shuffleCostValue + IOCost;
+  }
+
+  public CostInfo getExecutionCost(RelNode rel) {
+    if (rel instanceof TableScan) {
+      return getExecutionCostTableScan((TableScan) rel);
+    } else if (rel instanceof LogicalJoin) {
+      return getExecutionCostJoin((LogicalJoin) rel);
+    } else if (rel instanceof LogicalUnion) {
+      return getExecutionCostUnion((LogicalUnion) rel);
+    } else if (rel instanceof LogicalProject) {
+      return getExecutionCostProject((LogicalProject) rel);
+    }
+    return new CostInfo(0.0, 0.0);
+  }
+
+  private CostInfo getExecutionCostTableScan(TableScan scan) {
+    RelOptTable originalTable = scan.getTable();
+    String tableName = getTableName(originalTable);
+    try {
+      TableStatistic tableStat = costStatistic.get(tableName);
+      Double rowCount = tableStat.rowCount;
+      return new CostInfo(rowCount, rowCount);
+    } catch (NullPointerException e) {
+      throw new IllegalArgumentException("Table statistics not found for table: " + tableName);
+    }
+  }
+
+  private String getTableName(RelOptTable table) {
+    return String.join(".", table.getQualifiedName());
+  }
+
+  private CostInfo getExecutionCostJoin(LogicalJoin join) {
+    RelNode left = join.getLeft();
+    RelNode right = join.getRight();
+    CostInfo leftCost = getExecutionCost(left);
+    CostInfo rightCost = getExecutionCost(right);
+    Double joinSize = estimateJoinSize(join, leftCost.rowCount, rightCost.rowCount);
+    // The shuffle cost of a join is the maximum shuffle cost of its children because
+    // in modern distributed systems, the shuffle cost is dominated by the largest shuffle.
+    return new CostInfo(max(leftCost.shuffleCost, rightCost.shuffleCost), joinSize);
+  }
+
+  private List<JoinKey> getJoinKeys(LogicalJoin join) {
+    List<JoinKey> joinKeys = new ArrayList<>();
+    RexNode condition = join.getCondition();
+    if (condition instanceof RexCall) {
+      getJoinKeysFromJoinCondition((RexCall) condition, join, joinKeys);
+    }
+    // Assertion to check if joinKeys.size() is greater than or equal to 1
+    if (joinKeys.size() < 1) {
+      throw new IllegalArgumentException("Join keys size is less than 1");
+    }
+    return joinKeys;
+  }
+
+  private void getJoinKeysFromJoinCondition(RexCall call, LogicalJoin join, List<JoinKey> joinKeys) {
+    if (call.getOperator().getName().equalsIgnoreCase("AND")) {
+      // Process each operand of the AND separately
+      for (RexNode operand : call.getOperands()) {
+        if (operand instanceof RexCall) {
+          getJoinKeysFromJoinCondition((RexCall) operand, join, joinKeys);
+        }
+      }
+    } else {
+      // Process the join condition (e.g., EQUALS)
+      List<RexNode> operands = call.getOperands();
+      if (operands.size() == 2 && operands.get(0) instanceof RexInputRef && operands.get(1) instanceof RexInputRef) {
+        RexInputRef leftRef = (RexInputRef) operands.get(0);
+        RexInputRef rightRef = (RexInputRef) operands.get(1);
+        RelDataType leftType = join.getLeft().getRowType();
+        RelDataType rightType = join.getRight().getRowType();
+
+        int leftIndex = leftRef.getIndex();
+        int rightIndex = rightRef.getIndex() - leftType.getFieldCount();
+
+        RelDataTypeField leftField = leftType.getFieldList().get(leftIndex);
+        String leftTableName = getTableName(join.getLeft().getTable());
+        String leftFieldName = leftField.getName();
+        RelDataTypeField rightField = rightType.getFieldList().get(rightIndex);
+        String rightTableName = getTableName(join.getRight().getTable());
+        String rightFieldName = rightField.getName();
+
+        joinKeys.add(new JoinKey(leftTableName, rightTableName, leftFieldName, rightFieldName));
+      }
+    }
+  }
+
+  private Double estimateJoinSize(LogicalJoin join, Double leftSize, Double rightSize) {
+    List<JoinKey> joinKeys = getJoinKeys(join);
+    Double selectivity = 1.0;
+    for (JoinKey joinKey : joinKeys) {
+      String leftTableName = joinKey.leftTableName;
+      String rightTableName = joinKey.rightTableName;
+      String leftFieldName = joinKey.leftFieldName;
+      String rightFieldName = joinKey.rightFieldName;
+      try {
+        TableStatistic leftTableStat = costStatistic.get(leftTableName);
+        TableStatistic rightTableStat = costStatistic.get(rightTableName);
+        Double leftCardinality = leftTableStat.rowCount;
+        Double rightCardinality = rightTableStat.rowCount;
+        Double leftDistinct = leftTableStat.distinctCountByRow.getOrDefault(leftFieldName, leftCardinality);
+        Double rightDistinct = rightTableStat.distinctCountByRow.getOrDefault(rightFieldName, rightCardinality);
+        selectivity *= 1 / max(leftDistinct, rightDistinct);
+      } catch (NullPointerException e) {
+        throw new IllegalArgumentException(
+            "Table statistics not found for table: " + leftTableName + " or " + rightTableName);
+      }
+    }
+    return leftSize * rightSize * selectivity;
+  }
+
+  private CostInfo getExecutionCostUnion(LogicalUnion union) {
+    Double unionCost = 0.0;
+    Double unionSize = 0.0;
+    RelNode input;
+    for (Iterator var4 = union.getInputs().iterator(); var4.hasNext();) {
+      input = (RelNode) var4.next();
+      CostInfo inputCost = getExecutionCost(input);
+      unionSize += inputCost.rowCount;
+      unionCost = max(inputCost.shuffleCost, unionCost);
+    }
+    unionCost *= 2;
+    return new CostInfo(unionCost, unionSize);
+  }
+
+  private CostInfo getExecutionCostProject(LogicalProject project) {
+    return getExecutionCost(project.getInput());
+  }
+}

coral-incremental/src/main/java/com/linkedin/coral/incremental/TableStatistic.java

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+/**
+ * Copyright 2024 LinkedIn Corporation. All rights reserved.
+ * Licensed under the BSD-2 Clause license.
+ * See LICENSE in the project root for license information.
+ */
+package com.linkedin.coral.incremental;
+
+import java.util.Map;
+
+
+public class TableStatistic {
+  // The number of rows in the table
+  Double rowCount;
+  // The number of distinct values in each column
+  Map<String, Double> distinctCountByRow;
+}

coral-incremental/src/test/java/com/linkedin/coral/incremental/RelNodeCostEstimatorTest.java

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+/**
+ * Copyright 2024 LinkedIn Corporation. All rights reserved.
+ * Licensed under the BSD-2 Clause license.
+ * See LICENSE in the project root for license information.
+ */
+package com.linkedin.coral.incremental;
+
+import java.io.File;
+import java.io.IOException;
+import java.util.HashMap;
+import java.util.Map;
+
+import org.apache.calcite.rel.RelNode;
+import org.apache.commons.io.FileUtils;
+import org.apache.hadoop.hive.conf.HiveConf;
+import org.apache.hadoop.hive.metastore.api.MetaException;
+import org.apache.hadoop.hive.ql.metadata.HiveException;
+import org.testng.annotations.AfterTest;
+import org.testng.annotations.BeforeClass;
+import org.testng.annotations.Test;
+
+import static com.linkedin.coral.incremental.TestUtils.*;
+import static org.testng.Assert.*;
+
+
+public class RelNodeCostEstimatorTest {
+  private HiveConf conf;
+
+  private RelNodeCostEstimator estimator;
+
+  static final String TEST_JSON_FILE_DIR = "src/test/resources/";
+
+  @BeforeClass
+  public void beforeClass() throws HiveException, MetaException, IOException {
+    conf = TestUtils.loadResourceHiveConf();
+    estimator = new RelNodeCostEstimator(2.0, 1.0);
+    TestUtils.initializeViews(conf);
+  }
+
+  @AfterTest
+  public void afterClass() throws IOException {
+    FileUtils.deleteDirectory(new File(conf.get(CORAL_INCREMENTAL_TEST_DIR)));
+  }
+
+  public Map<String, Double> fakeStatData() {
+    Map<String, Double> stat = new HashMap<>();
+    stat.put("hive.test.bar1", 80.0);
+    stat.put("hive.test.bar2", 20.0);
+    stat.put("hive.test.bar1_prev", 40.0);
+    stat.put("hive.test.bar2_prev", 10.0);
+    stat.put("hive.test.bar1_delta", 60.0);
+    stat.put("hive.test.bar2_delta", 10.0);
+    return stat;
+  }
+
+  @Test
+  public void testSimpleSelectAll() throws IOException {
+    String sql = "SELECT * FROM test.bar1";
+    RelNode relNode = hiveToRelConverter.convertSql(sql);
+    estimator.loadStatistic(TEST_JSON_FILE_DIR + "statistic.json");
+    assertEquals(estimator.getCost(relNode), 300.0);
+    estimator.setStat(fakeStatData());
+    assertEquals(estimator.getCost(relNode), 240.0);
+  }
+
+  @Test
+  public void testSimpleJoin() throws IOException {
+    String sql = "SELECT * FROM test.bar1 JOIN test.bar2 ON test.bar1.x = test.bar2.x";
+    RelNode relNode = hiveToRelConverter.convertSql(sql);
+    estimator.loadStatistic(TEST_JSON_FILE_DIR + "statistic.json");
+    assertEquals(estimator.getCost(relNode), 500.0);
+    estimator.setStat(fakeStatData());
+    assertEquals(estimator.getCost(relNode), 400.0);
+  }
+}