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From Ben-Zvi <...@git.apache.org>
Subject [GitHub] drill pull request #717: DRILL-5080: Memory-managed version of external sort
Date Sat, 11 Feb 2017 02:39:11 GMT
Github user Ben-Zvi commented on a diff in the pull request:

    https://github.com/apache/drill/pull/717#discussion_r100657733
  
    --- Diff: exec/java-exec/src/main/java/org/apache/drill/exec/physical/impl/spill/RecordBatchSizer.java
---
    @@ -0,0 +1,293 @@
    +/*
    + * 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.physical.impl.spill;
    +
    +import java.util.ArrayList;
    +import java.util.List;
    +
    +import org.apache.drill.exec.expr.TypeHelper;
    +import org.apache.drill.exec.memory.BaseAllocator;
    +import org.apache.drill.exec.record.BatchSchema;
    +import org.apache.drill.exec.record.MaterializedField;
    +import org.apache.drill.exec.record.VectorAccessible;
    +import org.apache.drill.exec.record.VectorWrapper;
    +import org.apache.drill.exec.record.selection.SelectionVector2;
    +import org.apache.drill.exec.vector.BaseDataValueVector;
    +import org.apache.drill.exec.vector.FixedWidthVector;
    +import org.apache.drill.exec.vector.NullableVarCharVector;
    +import org.apache.drill.exec.vector.NullableVector;
    +import org.apache.drill.exec.vector.ValueVector;
    +import org.apache.drill.exec.vector.VarCharVector;
    +
    +import io.netty.buffer.DrillBuf;
    +
    +/**
    + * Given a record batch or vector container, determines the actual memory
    + * consumed by each column, the average row, and the entire record batch.
    + */
    +
    +public class RecordBatchSizer {
    +  private static final org.slf4j.Logger logger = org.slf4j.LoggerFactory.getLogger(RecordBatchSizer.class);
    +
    +  /**
    +   * Column size information.
    +   */
    +  public static class ColumnSize {
    +    public final MaterializedField metadata;
    +
    +    /**
    +     * Assumed size from Drill metadata.
    +     */
    +    public int stdSize;
    +    /**
    +     * Actual memory consumed by all the vectors associated with this column.
    +     */
    +    public int totalSize;
    +    /**
    +     * Actual average column width as determined from actual memory use. This
    +     * size is larger than the actual data size since this size includes per-
    +     * column overhead such as any unused vector space, etc.
    +     */
    +    public int estSize;
    +
    +    /**
    +     * The size of the data vector backing the column. Useful for detecting
    +     * cases of possible direct memory fragmentation.
    +     */
    +    public int dataVectorSize;
    +    public int capacity;
    +    public int density;
    +    public int dataSize;
    +
    +    @SuppressWarnings("resource")
    +    public ColumnSize(VectorWrapper<?> vw) {
    +      metadata = vw.getField();
    +      stdSize = TypeHelper.getSize(metadata.getType());
    +
    +      // Can't get size estimates if this is an empty batch.
    +
    +      ValueVector v = vw.getValueVector();
    +      int rowCount = v.getAccessor().getValueCount();
    +      if (rowCount == 0) {
    +        return;
    +      }
    +      DrillBuf[] bufs = v.getBuffers(false);
    +      for (DrillBuf buf : bufs) {
    +        totalSize += buf.capacity();
    +      }
    +
    +      // Capacity is the number of values that the vector could
    +      // contain. This is useful only for fixed-length vectors.
    +
    +      capacity = v.getValueCapacity();
    +
    +      // Crude way to get the size of the buffer underlying simple (scalar) values.
    +      // Ignores maps, lists and other esoterica. Uses a crude way to subtract out
    +      // the null "bit" (really byte) buffer size for nullable vectors.
    +
    +      if (v instanceof BaseDataValueVector) {
    +        dataVectorSize = totalSize;
    +        if (v instanceof NullableVector) {
    +          dataVectorSize -= bufs[0].getActualMemoryConsumed();
    +        }
    +      }
    +
    +      // Determine "density" the number of rows compared to potential
    +      // capacity. Low-density batches occur at block boundaries, ends
    +      // of files and so on. Low-density batches throw off our estimates
    +      // for Varchar columns because we don't know the actual number of
    +      // bytes consumed (that information is hidden behind the Varchar
    +      // implementation where we can't get at it.)
    +      //
    +      // A better solution is to have each vector do this calc rather
    +      // than trying to do it generically, but that increases the code
    +      // change footprint and slows the commit process.
    +
    +      if (v instanceof FixedWidthVector) {
    +        dataSize = stdSize * rowCount;
    +      } else if ( v instanceof VarCharVector ) {
    +        VarCharVector vv = (VarCharVector) v;
    +        dataSize = vv.getOffsetVector().getAccessor().get(rowCount);
    +      } else if ( v instanceof NullableVarCharVector ) {
    +        NullableVarCharVector vv = (NullableVarCharVector) v;
    +        dataSize = vv.getValuesVector().getOffsetVector().getAccessor().get(rowCount);
    +      } else {
    +        dataSize = 0;
    +      }
    +      if (dataSize > 0) {
    +        density = roundUp(dataSize * 100, dataVectorSize);
    +        estSize = roundUp(dataSize, rowCount);
    +      }
    +    }
    +
    +    @Override
    +    public String toString() {
    +      StringBuilder buf = new StringBuilder();
    +      buf.append(metadata.getName());
    +      buf.append("(std col. size: ");
    +      buf.append(stdSize);
    +      buf.append(", actual col. size: ");
    +      buf.append(estSize);
    +      buf.append(", total size: ");
    +      buf.append(totalSize);
    +      buf.append(", vector size: ");
    +      buf.append(dataVectorSize);
    +      buf.append(", data size: ");
    +      buf.append(dataSize);
    +      buf.append(", row capacity: ");
    +      buf.append(capacity);
    +      buf.append(", density: ");
    +      buf.append(density);
    +      buf.append(")");
    +      return buf.toString();
    +    }
    +  }
    +
    +  List<ColumnSize> columnSizes = new ArrayList<>();
    +
    +  /**
    +   * Number of records (rows) in the batch.
    +   */
    +  private int rowCount;
    +  /**
    +   * Standard row width using Drill meta-data.
    +   */
    +  private int stdRowWidth;
    +  /**
    +   * Actual batch size summing all buffers used to store data
    +   * for the batch.
    +   */
    +  private int totalBatchSize;
    +  /**
    +   * Actual row width computed by dividing total batch memory by the
    +   * record count.
    +   */
    +  private int grossRowWidth;
    +  /**
    +   * Actual row width computed by summing columns. Use this if the
    +   * vectors are partially full; prevents overestimating row width.
    +   */
    +  private int netRowWidth;
    +  private boolean hasSv2;
    +  private int sv2Size;
    +  private int avgDensity;
    +
    +  public RecordBatchSizer(VectorAccessible va) {
    +    rowCount = va.getRecordCount();
    +    for (VectorWrapper<?> vw : va) {
    +      measureField(vw);
    +    }
    +
    +    if (rowCount > 0) {
    +      grossRowWidth = roundUp(totalBatchSize, rowCount);
    +    }
    +
    +    hasSv2 = va.getSchema().getSelectionVectorMode() == BatchSchema.SelectionVectorMode.TWO_BYTE;
    +    if (hasSv2) {
    +      @SuppressWarnings("resource")
    +      SelectionVector2 sv2 = va.getSelectionVector2();
    +      sv2Size = sv2.getBuffer().capacity();
    +      grossRowWidth += sv2Size;
    +      netRowWidth += 2;
    +    }
    +
    +    int totalDensity = 0;
    +    int usableCount = 0;
    +    for (ColumnSize colSize : columnSizes) {
    +      if ( colSize.density > 0 ) {
    +        usableCount++;
    +      }
    +      totalDensity += colSize.density;
    +    }
    +    avgDensity = roundUp(totalDensity, usableCount);
    +  }
    +
    +  public void applySv2() {
    +    if (hasSv2) {
    +      return;
    +    }
    +
    +    sv2Size = BaseAllocator.nextPowerOfTwo(2 * rowCount);
    +    grossRowWidth += roundUp(sv2Size, rowCount);
    +    totalBatchSize += sv2Size;
    +  }
    +
    +  private void measureField(VectorWrapper<?> vw) {
    +    ColumnSize colSize = new ColumnSize(vw);
    +    columnSizes.add(colSize);
    +
    +    stdRowWidth += colSize.stdSize;
    +    totalBatchSize += colSize.totalSize;
    +    netRowWidth += colSize.estSize;
    +  }
    +
    +  public static int roundUp(int denom, int num) {
    +    if(num == 0) {
    +      return 0;
    +    }
    +    return (int) Math.ceil((double) denom / num);
    +  }
    +
    +  public int rowCount() { return rowCount; }
    +  public int stdRowWidth() { return stdRowWidth; }
    +  public int grossRowWidth() { return grossRowWidth; }
    +  public int netRowWidth() { return netRowWidth; }
    +  public int actualSize() { return totalBatchSize; }
    +  public boolean hasSv2() { return hasSv2; }
    +  public int getAvgDensity() { return avgDensity; }
    +
    +  public static final int MAX_VECTOR_SIZE = 16 * 1024 * 1024; // 16 MiB
    +
    +  /**
    +   * Look for columns backed by vectors larger than the 16 MiB size
    +   * employed by the Netty allocator. Such large blocks can lead to
    +   * memory fragmentation and unexpected OOM errors.
    +   * @return if any column is oversize
    --- End diff --
    
    @return "true" ... oversized


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