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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,
 * 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.cassandra.db;

import java.io.IOException;
import java.util.*;
import java.util.function.Consumer;
import java.util.function.Predicate;
import java.nio.ByteBuffer;

import com.google.common.collect.ImmutableList;
import com.google.common.collect.Iterators;

import net.nicoulaj.compilecommand.annotations.DontInline;
import org.apache.cassandra.schema.ColumnMetadata;
import org.apache.cassandra.schema.TableMetadata;
import org.apache.cassandra.cql3.ColumnIdentifier;
import org.apache.cassandra.db.marshal.SetType;
import org.apache.cassandra.db.marshal.UTF8Type;
import org.apache.cassandra.db.rows.ColumnData;
import org.apache.cassandra.db.rows.Row;
import org.apache.cassandra.io.util.DataInputPlus;
import org.apache.cassandra.io.util.DataOutputPlus;
import org.apache.cassandra.utils.ByteBufferUtil;
import org.apache.cassandra.utils.ObjectSizes;
import org.apache.cassandra.utils.SearchIterator;
import org.apache.cassandra.utils.btree.BTree;
import org.apache.cassandra.utils.btree.BTreeSearchIterator;
import org.apache.cassandra.utils.btree.BTreeRemoval;

/**
 * An immutable and sorted list of (non-PK) columns for a given table.
 * 

* Note that in practice, it will either store only static columns, or only regular ones. When * we need both type of columns, we use a {@link RegularAndStaticColumns} object. */ public class Columns extends AbstractCollection implements Collection { public static final Serializer serializer = new Serializer(); public static final Columns NONE = new Columns(BTree.empty(), 0); static final long EMPTY_SIZE = ObjectSizes.measure(NONE); public static final ColumnMetadata FIRST_COMPLEX_STATIC = new ColumnMetadata("", "", ColumnIdentifier.getInterned(ByteBufferUtil.EMPTY_BYTE_BUFFER, UTF8Type.instance), SetType.getInstance(UTF8Type.instance, true), ColumnMetadata.NO_POSITION, ColumnMetadata.Kind.STATIC); public static final ColumnMetadata FIRST_COMPLEX_REGULAR = new ColumnMetadata("", "", ColumnIdentifier.getInterned(ByteBufferUtil.EMPTY_BYTE_BUFFER, UTF8Type.instance), SetType.getInstance(UTF8Type.instance, true), ColumnMetadata.NO_POSITION, ColumnMetadata.Kind.REGULAR); private final Object[] columns; private final int complexIdx; // Index of the first complex column private Columns(Object[] columns, int complexIdx) { assert complexIdx <= BTree.size(columns); this.columns = columns; this.complexIdx = complexIdx; } private Columns(Object[] columns) { this(columns, findFirstComplexIdx(columns)); } /** * Creates a {@code Columns} holding only the one column provided. * * @param c the column for which to create a {@code Columns} object. * * @return the newly created {@code Columns} containing only {@code c}. */ public static Columns of(ColumnMetadata c) { return new Columns(BTree.singleton(c), c.isComplex() ? 0 : 1); } /** * Returns a new {@code Columns} object holing the same columns as the provided Row. * * @param row the row from which to create the new {@code Columns}. * @return the newly created {@code Columns} containing the columns from {@code row}. */ public static Columns from(Row row) { try (BTree.FastBuilder builder = BTree.fastBuilder()) { for (ColumnData cd : row) builder.add(cd.column()); Object[] tree = builder.build(); return new Columns(tree, findFirstComplexIdx(tree)); } } public static Columns from(BTree.Builder builder) { Object[] tree = builder.build(); return new Columns(tree, findFirstComplexIdx(tree)); } /** * Returns a new {@code Columns} object holding the same columns than the provided set. * This method assumes nothing about the order of {@code s}. * * @param s the set from which to create the new {@code Columns}. * @return the newly created {@code Columns} containing the columns from {@code s}. */ public static Columns from(Collection s) { Object[] tree = BTree.builder(Comparator.naturalOrder()).addAll(s).build(); return new Columns(tree, findFirstComplexIdx(tree)); } private static int findFirstComplexIdx(Object[] tree) { if (BTree.isEmpty(tree)) return 0; int size = BTree.size(tree); ColumnMetadata last = BTree.findByIndex(tree, size - 1); return last.isSimple() ? size : BTree.ceilIndex(tree, Comparator.naturalOrder(), last.isStatic() ? FIRST_COMPLEX_STATIC : FIRST_COMPLEX_REGULAR); } /** * Whether this columns is empty. * * @return whether this columns is empty. */ public boolean isEmpty() { return BTree.isEmpty(columns); } /** * The number of simple columns in this object. * * @return the number of simple columns in this object. */ public int simpleColumnCount() { return complexIdx; } /** * The number of complex columns (non-frozen collections, udts, ...) in this object. * * @return the number of complex columns in this object. */ public int complexColumnCount() { return BTree.size(columns) - complexIdx; } /** * The total number of columns in this object. * * @return the total number of columns in this object. */ public int size() { return BTree.size(columns); } /** * Whether this objects contains simple columns. * * @return whether this objects contains simple columns. */ public boolean hasSimple() { return complexIdx > 0; } /** * Whether this objects contains complex columns. * * @return whether this objects contains complex columns. */ public boolean hasComplex() { return complexIdx < BTree.size(columns); } /** * Returns the ith simple column of this object. * * @param i the index for the simple column to fectch. This must * satisfy {@code 0 <= i < simpleColumnCount()}. * * @return the {@code i}th simple column in this object. */ public ColumnMetadata getSimple(int i) { return BTree.findByIndex(columns, i); } /** * Returns the ith complex column of this object. * * @param i the index for the complex column to fectch. This must * satisfy {@code 0 <= i < complexColumnCount()}. * * @return the {@code i}th complex column in this object. */ public ColumnMetadata getComplex(int i) { return BTree.findByIndex(columns, complexIdx + i); } /** * The index of the provided simple column in this object (if it contains * the provided column). * * @param c the simple column for which to return the index of. * * @return the index for simple column {@code c} if it is contains in this * object */ public int simpleIdx(ColumnMetadata c) { return BTree.findIndex(columns, Comparator.naturalOrder(), c); } /** * The index of the provided complex column in this object (if it contains * the provided column). * * @param c the complex column for which to return the index of. * * @return the index for complex column {@code c} if it is contains in this * object */ public int complexIdx(ColumnMetadata c) { return BTree.findIndex(columns, Comparator.naturalOrder(), c) - complexIdx; } /** * Whether the provided column is contained by this object. * * @param c the column to check presence of. * * @return whether {@code c} is contained by this object. */ public boolean contains(ColumnMetadata c) { return BTree.findIndex(columns, Comparator.naturalOrder(), c) >= 0; } /** * Returns the result of merging this {@code Columns} object with the * provided one. * * @param other the other {@code Columns} to merge this object with. * * @return the result of merging/taking the union of {@code this} and * {@code other}. The returned object may be one of the operand and that * operand is a subset of the other operand. */ public Columns mergeTo(Columns other) { if (this == other || other == NONE) return this; if (this == NONE) return other; Object[] tree = BTree.update(this.columns, other.columns, Comparator.naturalOrder()); if (tree == this.columns) return this; if (tree == other.columns) return other; return new Columns(tree, findFirstComplexIdx(tree)); } /** * Whether this object is a superset of the provided other {@code Columns object}. * * @param other the other object to test for inclusion in this object. * * @return whether all the columns of {@code other} are contained by this object. */ public boolean containsAll(Collection other) { if (other == this) return true; if (other.size() > this.size()) return false; BTreeSearchIterator iter = BTree.slice(columns, Comparator.naturalOrder(), BTree.Dir.ASC); for (Object def : other) if (iter.next((ColumnMetadata) def) == null) return false; return true; } /** * Iterator over the simple columns of this object. * * @return an iterator over the simple columns of this object. */ public Iterator simpleColumns() { return BTree.iterator(columns, 0, complexIdx - 1, BTree.Dir.ASC); } /** * Iterator over the complex columns of this object. * * @return an iterator over the complex columns of this object. */ public Iterator complexColumns() { return BTree.iterator(columns, complexIdx, BTree.size(columns) - 1, BTree.Dir.ASC); } /** * Iterator over all the columns of this object. * * @return an iterator over all the columns of this object. */ public BTreeSearchIterator iterator() { return BTree.slice(columns, Comparator.naturalOrder(), BTree.Dir.ASC); } /** * An iterator that returns the columns of this object in "select" order (that * is in global alphabetical order, where the "normal" iterator returns simple * columns first and the complex second). * * @return an iterator returning columns in alphabetical order. */ public Iterator selectOrderIterator() { // In wildcard selection, we want to return all columns in alphabetical order, // irregarding of whether they are complex or not return Iterators. mergeSorted(ImmutableList.of(simpleColumns(), complexColumns()), (s, c) -> { assert !s.kind.isPrimaryKeyKind(); return s.name.bytes.compareTo(c.name.bytes); }); } /** * Returns the equivalent of those columns but with the provided column removed. * * @param column the column to remove. * * @return newly allocated columns containing all the columns of {@code this} expect * for {@code column}. */ public Columns without(ColumnMetadata column) { if (!contains(column)) return this; Object[] newColumns = BTreeRemoval.remove(columns, Comparator.naturalOrder(), column); return new Columns(newColumns); } /** * Returns a predicate to test whether columns are included in this {@code Columns} object, * assuming that tes tested columns are passed to the predicate in sorted order. * * @return a predicate to test the inclusion of sorted columns in this object. */ public Predicate inOrderInclusionTester() { SearchIterator iter = BTree.slice(columns, Comparator.naturalOrder(), BTree.Dir.ASC); return column -> iter.next(column) != null; } public void digest(Digest digest) { for (ColumnMetadata c : this) digest.update(c.name.bytes); } /** * Apply a function to each column definition in forwards or reversed order. * @param function */ public void apply(Consumer function) { BTree.apply(columns, function); } @Override public boolean equals(Object other) { if (other == this) return true; if (!(other instanceof Columns)) return false; Columns that = (Columns)other; return this.complexIdx == that.complexIdx && BTree.equals(this.columns, that.columns); } @Override public int hashCode() { return Objects.hash(complexIdx, BTree.hashCode(columns)); } public long unsharedHeapSize() { if(this == NONE) return 0; return EMPTY_SIZE + BTree.sizeOfStructureOnHeap(columns); } @Override public String toString() { StringBuilder sb = new StringBuilder("["); boolean first = true; for (ColumnMetadata def : this) { if (first) first = false; else sb.append(" "); sb.append(def.name); } return sb.append("]").toString(); } public static class Serializer { public void serialize(Columns columns, DataOutputPlus out) throws IOException { out.writeUnsignedVInt(columns.size()); for (ColumnMetadata column : columns) ByteBufferUtil.writeWithVIntLength(column.name.bytes, out); } public long serializedSize(Columns columns) { long size = TypeSizes.sizeofUnsignedVInt(columns.size()); for (ColumnMetadata column : columns) size += ByteBufferUtil.serializedSizeWithVIntLength(column.name.bytes); return size; } public Columns deserialize(DataInputPlus in, TableMetadata metadata) throws IOException { int length = (int)in.readUnsignedVInt(); try (BTree.FastBuilder builder = BTree.fastBuilder()) { for (int i = 0; i < length; i++) { ByteBuffer name = ByteBufferUtil.readWithVIntLength(in); ColumnMetadata column = metadata.getColumn(name); if (column == null) { // If we don't find the definition, it could be we have data for a dropped column, and we shouldn't // fail deserialization because of that. So we grab a "fake" ColumnMetadata that ensure proper // deserialization. The column will be ignore later on anyway. column = metadata.getDroppedColumn(name); if (column == null) throw new RuntimeException("Unknown column " + UTF8Type.instance.getString(name) + " during deserialization"); } builder.add(column); } return new Columns(builder.build()); } } /** * If both ends have a pre-shared superset of the columns we are serializing, we can send them much * more efficiently. Both ends must provide the identically same set of columns. */ public void serializeSubset(Collection columns, Columns superset, DataOutputPlus out) throws IOException { /** * We weight this towards small sets, and sets where the majority of items are present, since * we expect this to mostly be used for serializing result sets. * * For supersets with fewer than 64 columns, we encode a bitmap of *missing* columns, * which equates to a zero (single byte) when all columns are present, and otherwise * a positive integer that can typically be vint encoded efficiently. * * If we have 64 or more columns, we cannot neatly perform a bitmap encoding, so we just switch * to a vint encoded set of deltas, either adding or subtracting (whichever is most efficient). * We indicate this switch by sending our bitmap with every bit set, i.e. -1L */ int columnCount = columns.size(); int supersetCount = superset.size(); if (columnCount == supersetCount) { out.writeUnsignedVInt(0); } else if (supersetCount < 64) { out.writeUnsignedVInt(encodeBitmap(columns, superset, supersetCount)); } else { serializeLargeSubset(columns, columnCount, superset, supersetCount, out); } } public long serializedSubsetSize(Collection columns, Columns superset) { int columnCount = columns.size(); int supersetCount = superset.size(); if (columnCount == supersetCount) { return TypeSizes.sizeofUnsignedVInt(0); } else if (supersetCount < 64) { return TypeSizes.sizeofUnsignedVInt(encodeBitmap(columns, superset, supersetCount)); } else { return serializeLargeSubsetSize(columns, columnCount, superset, supersetCount); } } public Columns deserializeSubset(Columns superset, DataInputPlus in) throws IOException { long encoded = in.readUnsignedVInt(); if (encoded == 0L) { return superset; } else if (superset.size() >= 64) { return deserializeLargeSubset(in, superset, (int) encoded); } else { try (BTree.FastBuilder builder = BTree.fastBuilder()) { int firstComplexIdx = 0; for (ColumnMetadata column : superset) { if ((encoded & 1) == 0) { builder.add(column); if (column.isSimple()) ++firstComplexIdx; } encoded >>>= 1; } if (encoded != 0) throw new IOException("Invalid Columns subset bytes; too many bits set:" + Long.toBinaryString(encoded)); return new Columns(builder.build(), firstComplexIdx); } } } // encodes a 1 bit for every *missing* column, on the assumption presence is more common, // and because this is consistent with encoding 0 to represent all present private static long encodeBitmap(Collection columns, Columns superset, int supersetCount) { long bitmap = 0L; BTreeSearchIterator iter = superset.iterator(); // the index we would encounter next if all columns are present int expectIndex = 0; for (ColumnMetadata column : columns) { if (iter.next(column) == null) throw new IllegalStateException(columns + " is not a subset of " + superset); int currentIndex = iter.indexOfCurrent(); int count = currentIndex - expectIndex; // (1L << count) - 1 gives us count bits set at the bottom of the register // so << expectIndex moves these bits to start at expectIndex, which is where our missing portion // begins (assuming count > 0; if not, we're adding 0 bits, so it's a no-op) bitmap |= ((1L << count) - 1) << expectIndex; expectIndex = currentIndex + 1; } int count = supersetCount - expectIndex; bitmap |= ((1L << count) - 1) << expectIndex; return bitmap; } @DontInline private void serializeLargeSubset(Collection columns, int columnCount, Columns superset, int supersetCount, DataOutputPlus out) throws IOException { // write flag indicating we're in lengthy mode out.writeUnsignedVInt(supersetCount - columnCount); BTreeSearchIterator iter = superset.iterator(); if (columnCount < supersetCount / 2) { // write present columns for (ColumnMetadata column : columns) { if (iter.next(column) == null) throw new IllegalStateException(); out.writeUnsignedVInt(iter.indexOfCurrent()); } } else { // write missing columns int prev = -1; for (ColumnMetadata column : columns) { if (iter.next(column) == null) throw new IllegalStateException(); int cur = iter.indexOfCurrent(); while (++prev != cur) out.writeUnsignedVInt(prev); } while (++prev != supersetCount) out.writeUnsignedVInt(prev); } } @DontInline private Columns deserializeLargeSubset(DataInputPlus in, Columns superset, int delta) throws IOException { int supersetCount = superset.size(); int columnCount = supersetCount - delta; try (BTree.FastBuilder builder = BTree.fastBuilder()) { if (columnCount < supersetCount / 2) { for (int i = 0 ; i < columnCount ; i++) { int idx = (int) in.readUnsignedVInt(); builder.add(BTree.findByIndex(superset.columns, idx)); } } else { Iterator iter = superset.iterator(); int idx = 0; int skipped = 0; while (true) { int nextMissingIndex = skipped < delta ? (int)in.readUnsignedVInt() : supersetCount; while (idx < nextMissingIndex) { ColumnMetadata def = iter.next(); builder.add(def); idx++; } if (idx == supersetCount) break; iter.next(); idx++; skipped++; } } return new Columns(builder.build()); } } @DontInline private int serializeLargeSubsetSize(Collection columns, int columnCount, Columns superset, int supersetCount) { // write flag indicating we're in lengthy mode int size = TypeSizes.sizeofUnsignedVInt(supersetCount - columnCount); BTreeSearchIterator iter = superset.iterator(); if (columnCount < supersetCount / 2) { // write present columns for (ColumnMetadata column : columns) { if (iter.next(column) == null) throw new IllegalStateException(); size += TypeSizes.sizeofUnsignedVInt(iter.indexOfCurrent()); } } else { // write missing columns int prev = -1; for (ColumnMetadata column : columns) { if (iter.next(column) == null) throw new IllegalStateException(); int cur = iter.indexOfCurrent(); while (++prev != cur) size += TypeSizes.sizeofUnsignedVInt(prev); } while (++prev != supersetCount) size += TypeSizes.sizeofUnsignedVInt(prev); } return size; } } }





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