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The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model.

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/*
 * 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,
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 * See the License for the specific language governing permissions and
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package org.apache.cassandra.db;

import java.io.IOException;
import java.nio.ByteBuffer;
import java.util.*;

import com.google.common.base.Preconditions;
import com.google.common.collect.Iterators;

import org.apache.cassandra.schema.ColumnMetadata;
import org.apache.cassandra.schema.TableMetadata;
import org.apache.cassandra.db.marshal.AbstractType;
import org.apache.cassandra.io.util.DataInputPlus;
import org.apache.cassandra.io.util.DataOutputPlus;

/**
 * Represents the selection of multiple range of rows within a partition.
 * 

* A {@code Slices} is basically a list of {@code Slice}, though those are guaranteed to be non-overlapping * and always in clustering order. */ public abstract class Slices implements Iterable { public static final Serializer serializer = new Serializer(); /** Slices selecting all the rows of a partition. */ public static final Slices ALL = new SelectAllSlices(); /** Slices selecting no rows in a partition. */ public static final Slices NONE = new SelectNoSlices(); protected Slices() { } /** * Creates a {@code Slices} object that contains a single slice. * * @param comparator the comparator for the table {@code slice} is a slice of. * @param slice the single slice that the return object should contains. * * @return the newly created {@code Slices} object. */ public static Slices with(ClusteringComparator comparator, Slice slice) { if (slice.start().isBottom() && slice.end().isTop()) return Slices.ALL; Preconditions.checkArgument(!slice.isEmpty(comparator)); return new ArrayBackedSlices(comparator, new Slice[]{ slice }); } /** * Whether the slices has a lower bound, that is whether it's first slice start is {@code Slice.BOTTOM}. * * @return whether the slices has a lower bound. */ public abstract boolean hasLowerBound(); /** * Whether the slices has an upper bound, that is whether it's last slice end is {@code Slice.TOP}. * * @return whether the slices has an upper bound. */ public abstract boolean hasUpperBound(); /** * The number of slice this object contains. * * @return the number of slice this object contains. */ public abstract int size(); /** * Returns the ith slice of this {@code Slices} object. * * @return the ith slice of this object. */ public abstract Slice get(int i); /** * Returns slices for continuing the paging of those slices given the last returned clustering prefix. * * @param comparator the comparator for the table this is a filter for. * @param lastReturned the last clustering that was returned for the query we are paging for. The * resulting slices will be such that only results coming stricly after {@code lastReturned} are returned * (where coming after means "greater than" if {@code !reversed} and "lesser than" otherwise). * @param inclusive whether or not we want to include the {@code lastReturned} in the newly returned page of results. * @param reversed whether the query we're paging for is reversed or not. * * @return new slices that select results coming after {@code lastReturned}. */ public abstract Slices forPaging(ClusteringComparator comparator, Clustering lastReturned, boolean inclusive, boolean reversed); /** * An object that allows to test whether rows are selected by this {@code Slices} objects assuming those rows * are tested in clustering order. * * @param reversed if true, the rows passed to the returned object will be assumed to be in reversed clustering * order, otherwise they should be in clustering order. * * @return an object that tests for selection of rows by this {@code Slices} object. */ public abstract InOrderTester inOrderTester(boolean reversed); /** * Whether a given clustering (row) is selected by this {@code Slices} object. * * @param clustering the clustering to test for selection. * * @return whether a given clustering (row) is selected by this {@code Slices} object. */ public abstract boolean selects(Clustering clustering); /** * Given the per-clustering column minimum and maximum value a sstable contains, whether or not this slices potentially * intersects that sstable or not. * * @param minClusteringValues the smallest values for each clustering column that a sstable contains. * @param maxClusteringValues the biggest values for each clustering column that a sstable contains. * * @return whether the slices might intersects with the sstable having {@code minClusteringValues} and * {@code maxClusteringValues}. */ public abstract boolean intersects(List minClusteringValues, List maxClusteringValues); public abstract String toCQLString(TableMetadata metadata); /** * Checks if this Slices is empty. * @return true if this Slices is empty, false otherwise. */ public final boolean isEmpty() { return size() == 0; } /** * In simple object that allows to test the inclusion of rows in those slices assuming those rows * are passed (to {@link #includes}) in clustering order (or reverse clustering ordered, depending * of the argument passed to {@link #inOrderTester}). */ public interface InOrderTester { public boolean includes(Clustering value); public boolean isDone(); } /** * Builder to create {@code Slices} objects. */ public static class Builder { private final ClusteringComparator comparator; private final List slices; private boolean needsNormalizing; public Builder(ClusteringComparator comparator) { this.comparator = comparator; this.slices = new ArrayList<>(); } public Builder(ClusteringComparator comparator, int initialSize) { this.comparator = comparator; this.slices = new ArrayList<>(initialSize); } public Builder add(ClusteringBound start, ClusteringBound end) { return add(Slice.make(start, end)); } public Builder add(Slice slice) { Preconditions.checkArgument(!slice.isEmpty(comparator)); if (slices.size() > 0 && comparator.compare(slices.get(slices.size()-1).end(), slice.start()) > 0) needsNormalizing = true; slices.add(slice); return this; } public Builder addAll(Slices slices) { for (Slice slice : slices) add(slice); return this; } public int size() { return slices.size(); } public Slices build() { if (slices.isEmpty()) return NONE; if (slices.size() == 1 && slices.get(0) == Slice.ALL) return ALL; List normalized = needsNormalizing ? normalize(slices) : slices; return new ArrayBackedSlices(comparator, normalized.toArray(new Slice[normalized.size()])); } /** * Given an array of slices (potentially overlapping and in any order) and return an equivalent array * of non-overlapping slices in clustering order. * * @param slices an array of slices. This may be modified by this method. * @return the smallest possible array of non-overlapping slices in clustering order. If the original * slices are already non-overlapping and in comparator order, this may or may not return the provided slices * directly. */ private List normalize(List slices) { if (slices.size() <= 1) return slices; Collections.sort(slices, new Comparator() { @Override public int compare(Slice s1, Slice s2) { int c = comparator.compare(s1.start(), s2.start()); if (c != 0) return c; return comparator.compare(s1.end(), s2.end()); } }); List slicesCopy = new ArrayList<>(slices.size()); Slice last = slices.get(0); for (int i = 1; i < slices.size(); i++) { Slice s2 = slices.get(i); boolean includesStart = last.includes(comparator, s2.start()); boolean includesFinish = last.includes(comparator, s2.end()); if (includesStart && includesFinish) continue; if (!includesStart && !includesFinish) { slicesCopy.add(last); last = s2; continue; } if (includesStart) { last = Slice.make(last.start(), s2.end()); continue; } assert !includesFinish; } slicesCopy.add(last); return slicesCopy; } } public static class Serializer { public void serialize(Slices slices, DataOutputPlus out, int version) throws IOException { int size = slices.size(); out.writeUnsignedVInt(size); if (size == 0) return; List> types = slices == ALL ? Collections.>emptyList() : ((ArrayBackedSlices)slices).comparator.subtypes(); for (Slice slice : slices) Slice.serializer.serialize(slice, out, version, types); } public long serializedSize(Slices slices, int version) { long size = TypeSizes.sizeofUnsignedVInt(slices.size()); if (slices.size() == 0) return size; List> types = slices instanceof SelectAllSlices ? Collections.>emptyList() : ((ArrayBackedSlices)slices).comparator.subtypes(); for (Slice slice : slices) size += Slice.serializer.serializedSize(slice, version, types); return size; } public Slices deserialize(DataInputPlus in, int version, TableMetadata metadata) throws IOException { int size = (int)in.readUnsignedVInt(); if (size == 0) return NONE; Slice[] slices = new Slice[size]; for (int i = 0; i < size; i++) slices[i] = Slice.serializer.deserialize(in, version, metadata.comparator.subtypes()); if (size == 1 && slices[0].start().isBottom() && slices[0].end().isTop()) return ALL; return new ArrayBackedSlices(metadata.comparator, slices); } } /** * Simple {@code Slices} implementation that stores its slices in an array. */ private static class ArrayBackedSlices extends Slices { private final ClusteringComparator comparator; private final Slice[] slices; private ArrayBackedSlices(ClusteringComparator comparator, Slice[] slices) { this.comparator = comparator; this.slices = slices; } public int size() { return slices.length; } public boolean hasLowerBound() { return slices[0].start().size() != 0; } public boolean hasUpperBound() { return slices[slices.length - 1].end().size() != 0; } public Slice get(int i) { return slices[i]; } public boolean selects(Clustering clustering) { for (int i = 0; i < slices.length; i++) { Slice slice = slices[i]; if (comparator.compare(clustering, slice.start()) < 0) return false; if (comparator.compare(clustering, slice.end()) <= 0) return true; } return false; } public InOrderTester inOrderTester(boolean reversed) { return reversed ? new InReverseOrderTester() : new InForwardOrderTester(); } public Slices forPaging(ClusteringComparator comparator, Clustering lastReturned, boolean inclusive, boolean reversed) { return reversed ? forReversePaging(comparator, lastReturned, inclusive) : forForwardPaging(comparator, lastReturned, inclusive); } private Slices forForwardPaging(ClusteringComparator comparator, Clustering lastReturned, boolean inclusive) { for (int i = 0; i < slices.length; i++) { Slice slice = slices[i]; Slice newSlice = slice.forPaging(comparator, lastReturned, inclusive, false); if (newSlice == null) continue; if (slice == newSlice && i == 0) return this; ArrayBackedSlices newSlices = new ArrayBackedSlices(comparator, Arrays.copyOfRange(slices, i, slices.length)); newSlices.slices[0] = newSlice; return newSlices; } return Slices.NONE; } private Slices forReversePaging(ClusteringComparator comparator, Clustering lastReturned, boolean inclusive) { for (int i = slices.length - 1; i >= 0; i--) { Slice slice = slices[i]; Slice newSlice = slice.forPaging(comparator, lastReturned, inclusive, true); if (newSlice == null) continue; if (slice == newSlice && i == slices.length - 1) return this; ArrayBackedSlices newSlices = new ArrayBackedSlices(comparator, Arrays.copyOfRange(slices, 0, i + 1)); newSlices.slices[i] = newSlice; return newSlices; } return Slices.NONE; } public boolean intersects(List minClusteringValues, List maxClusteringValues) { for (Slice slice : this) { if (slice.intersects(comparator, minClusteringValues, maxClusteringValues)) return true; } return false; } public Iterator iterator() { return Iterators.forArray(slices); } private class InForwardOrderTester implements InOrderTester { private int idx; private boolean inSlice; public boolean includes(Clustering value) { while (idx < slices.length) { if (!inSlice) { int cmp = comparator.compare(value, slices[idx].start()); // value < start if (cmp < 0) return false; inSlice = true; if (cmp == 0) return true; } // Here, start < value and inSlice if (comparator.compare(value, slices[idx].end()) <= 0) return true; ++idx; inSlice = false; } return false; } public boolean isDone() { return idx >= slices.length; } } private class InReverseOrderTester implements InOrderTester { private int idx; private boolean inSlice; public InReverseOrderTester() { this.idx = slices.length - 1; } public boolean includes(Clustering value) { while (idx >= 0) { if (!inSlice) { int cmp = comparator.compare(slices[idx].end(), value); // value > end if (cmp > 0) return false; inSlice = true; if (cmp == 0) return true; } // Here, value <= end and inSlice if (comparator.compare(slices[idx].start(), value) <= 0) return true; --idx; inSlice = false; } return false; } public boolean isDone() { return idx < 0; } } @Override public String toString() { StringBuilder sb = new StringBuilder(); sb.append("{"); for (int i = 0; i < slices.length; i++) { if (i > 0) sb.append(", "); sb.append(slices[i].toString(comparator)); } return sb.append("}").toString(); } public String toCQLString(TableMetadata metadata) { StringBuilder sb = new StringBuilder(); // In CQL, condition are expressed by column, so first group things that way, // i.e. for each column, we create a list of what each slice contains on that column int clusteringSize = metadata.clusteringColumns().size(); List> columnComponents = new ArrayList<>(clusteringSize); for (int i = 0; i < clusteringSize; i++) { List perSlice = new ArrayList<>(); columnComponents.add(perSlice); for (int j = 0; j < slices.length; j++) { ComponentOfSlice c = ComponentOfSlice.fromSlice(i, slices[j]); if (c != null) perSlice.add(c); } } boolean needAnd = false; for (int i = 0; i < clusteringSize; i++) { ColumnMetadata column = metadata.clusteringColumns().get(i); List componentInfo = columnComponents.get(i); if (componentInfo.isEmpty()) break; // For a given column, there is only 3 cases that CQL currently generates: // 1) every slice are EQ with the same value, it's a simple '=' relation. // 2) every slice are EQ but with different values, it's a IN relation. // 3) every slice aren't EQ but have the same values, we have inequality relations. // Note that this doesn't cover everything that ReadCommand can express, but // as it's all that CQL support for now, we'll ignore other cases (which would then // display a bogus query but that's not the end of the world). // TODO: we should improve this at some point. ComponentOfSlice first = componentInfo.get(0); if (first.isEQ()) { if (needAnd) sb.append(" AND "); needAnd = true; sb.append(column.name); Set values = new LinkedHashSet<>(); for (int j = 0; j < componentInfo.size(); j++) values.add(componentInfo.get(j).startValue); if (values.size() == 1) { sb.append(" = ").append(column.type.getString(first.startValue)); } else { sb.append(" IN ("); int j = 0; for (ByteBuffer value : values) sb.append(j++ == 0 ? "" : ", ").append(column.type.getString(value)); sb.append(")"); } } else { boolean isReversed = column.isReversedType(); // As said above, we assume (without checking) that this means all ComponentOfSlice for this column // are the same, so we only bother about the first. if (first.startValue != null) { if (needAnd) sb.append(" AND "); needAnd = true; sb.append(column.name); if (isReversed) sb.append(first.startInclusive ? " <= " : " < "); else sb.append(first.startInclusive ? " >= " : " > "); sb.append(column.type.getString(first.startValue)); } if (first.endValue != null) { if (needAnd) sb.append(" AND "); needAnd = true; sb.append(column.name); if (isReversed) sb.append(first.endInclusive ? " >= " : " > "); else sb.append(first.endInclusive ? " <= " : " < "); sb.append(column.type.getString(first.endValue)); } } } return sb.toString(); } // An somewhat adhoc utility class only used by nameAsCQLString private static class ComponentOfSlice { public final boolean startInclusive; public final ByteBuffer startValue; public final boolean endInclusive; public final ByteBuffer endValue; private ComponentOfSlice(boolean startInclusive, ByteBuffer startValue, boolean endInclusive, ByteBuffer endValue) { this.startInclusive = startInclusive; this.startValue = startValue; this.endInclusive = endInclusive; this.endValue = endValue; } public static ComponentOfSlice fromSlice(int component, Slice slice) { ClusteringBound start = slice.start(); ClusteringBound end = slice.end(); if (component >= start.size() && component >= end.size()) return null; boolean startInclusive = true, endInclusive = true; ByteBuffer startValue = null, endValue = null; if (component < start.size()) { startInclusive = start.isInclusive(); startValue = start.bufferAt(component); } if (component < end.size()) { endInclusive = end.isInclusive(); endValue = end.bufferAt(component); } return new ComponentOfSlice(startInclusive, startValue, endInclusive, endValue); } public boolean isEQ() { return Objects.equals(startValue, endValue); } } } /** * Specialized implementation of {@code Slices} that selects all rows. *

* This is equivalent to having the single {@code Slice.ALL} slice, but is somewhat more effecient. */ private static class SelectAllSlices extends Slices { private static final InOrderTester trivialTester = new InOrderTester() { public boolean includes(Clustering value) { return true; } public boolean isDone() { return false; } }; public int size() { return 1; } public Slice get(int i) { return Slice.ALL; } public boolean hasLowerBound() { return false; } public boolean hasUpperBound() { return false; } public boolean selects(Clustering clustering) { return true; } public Slices forPaging(ClusteringComparator comparator, Clustering lastReturned, boolean inclusive, boolean reversed) { return new ArrayBackedSlices(comparator, new Slice[]{ Slice.ALL.forPaging(comparator, lastReturned, inclusive, reversed) }); } public InOrderTester inOrderTester(boolean reversed) { return trivialTester; } public boolean intersects(List minClusteringValues, List maxClusteringValues) { return true; } public Iterator iterator() { return Iterators.singletonIterator(Slice.ALL); } @Override public String toString() { return "ALL"; } public String toCQLString(TableMetadata metadata) { return ""; } } /** * Specialized implementation of {@code Slices} that selects no rows. */ private static class SelectNoSlices extends Slices { private static final InOrderTester trivialTester = new InOrderTester() { public boolean includes(Clustering value) { return false; } public boolean isDone() { return true; } }; public int size() { return 0; } public Slice get(int i) { throw new UnsupportedOperationException(); } public boolean hasLowerBound() { return false; } public boolean hasUpperBound() { return false; } public Slices forPaging(ClusteringComparator comparator, Clustering lastReturned, boolean inclusive, boolean reversed) { return this; } public boolean selects(Clustering clustering) { return false; } public InOrderTester inOrderTester(boolean reversed) { return trivialTester; } public boolean intersects(List minClusteringValues, List maxClusteringValues) { return false; } public Iterator iterator() { return Collections.emptyIterator(); } @Override public String toString() { return "NONE"; } public String toCQLString(TableMetadata metadata) { return ""; } } }





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