/*
* 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.hadoop.hbase.io.compress;
import org.apache.yetus.audience.InterfaceAudience;
@InterfaceAudience.Private
public final class CompressionUtil {
private CompressionUtil() { }
/**
* Round up to the next power of two, unless the value would become negative (ints
* are signed), in which case just return Integer.MAX_VALUE.
*/
public static int roundInt2(int v) {
v = Integer.highestOneBit(v) << 1;
if (v < 0) {
return Integer.MAX_VALUE;
}
return v;
}
/**
* Most compression algorithms can be presented with pathological input that causes an
* expansion rather than a compression. Hadoop's compression API requires that we calculate
* additional buffer space required for the worst case. There is a formula developed for
* gzip that applies as a ballpark to all LZ variants. It should be good enough for now and
* has been tested as such with a range of different inputs.
*/
public static int compressionOverhead(int bufferSize) {
// Given an input buffer of 'buffersize' bytes we presume a worst case expansion of
// 32 bytes (block header) and addition 1/6th of the input size.
return (bufferSize / 6) + 32;
}
}