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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.hadoop.hbase.util;
import java.io.IOException;
import java.math.BigInteger;
import java.util.Arrays;
import java.util.Collection;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.TreeMap;
import org.apache.commons.lang3.ArrayUtils;
import org.apache.commons.lang3.StringUtils;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.HConstants;
import org.apache.hadoop.hbase.HRegionInfo;
import org.apache.hadoop.hbase.HRegionLocation;
import org.apache.hadoop.hbase.MetaTableAccessor;
import org.apache.hadoop.hbase.ServerName;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.ColumnFamilyDescriptor;
import org.apache.hadoop.hbase.client.TableDescriptor;
import org.apache.yetus.audience.InterfaceAudience;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.apache.hadoop.hbase.client.Admin;
import org.apache.hadoop.hbase.client.ClusterConnection;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.ConnectionFactory;
import org.apache.hadoop.hbase.client.NoServerForRegionException;
import org.apache.hadoop.hbase.client.RegionLocator;
import org.apache.hadoop.hbase.client.Table;
import org.apache.hadoop.hbase.regionserver.HRegionFileSystem;
import org.apache.hadoop.hbase.client.ColumnFamilyDescriptorBuilder;
import org.apache.hadoop.hbase.client.TableDescriptorBuilder;
import org.apache.hbase.thirdparty.com.google.common.base.Preconditions;
import org.apache.hbase.thirdparty.com.google.common.collect.Lists;
import org.apache.hbase.thirdparty.com.google.common.collect.Maps;
import org.apache.hbase.thirdparty.com.google.common.collect.Sets;
import org.apache.hbase.thirdparty.org.apache.commons.cli.CommandLine;
import org.apache.hbase.thirdparty.org.apache.commons.cli.GnuParser;
import org.apache.hbase.thirdparty.org.apache.commons.cli.HelpFormatter;
import org.apache.hbase.thirdparty.org.apache.commons.cli.OptionBuilder;
import org.apache.hbase.thirdparty.org.apache.commons.cli.Options;
import org.apache.hbase.thirdparty.org.apache.commons.cli.ParseException;
/**
* The {@link RegionSplitter} class provides several utilities to help in the
* administration lifecycle for developers who choose to manually split regions
* instead of having HBase handle that automatically. The most useful utilities
* are:
*
*
* - Create a table with a specified number of pre-split regions
*
- Execute a rolling split of all regions on an existing table
*
*
* Both operations can be safely done on a live server.
*
* Question: How do I turn off automatic splitting?
* Answer: Automatic splitting is determined by the configuration value
* HConstants.HREGION_MAX_FILESIZE. It is not recommended that you set this
* to Long.MAX_VALUE in case you forget about manual splits. A suggested setting
* is 100GB, which would result in > 1hr major compactions if reached.
*
* Question: Why did the original authors decide to manually split?
* Answer: Specific workload characteristics of our use case allowed us
* to benefit from a manual split system.
*
*
* - Data (~1k) that would grow instead of being replaced
*
- Data growth was roughly uniform across all regions
*
- OLTP workload. Data loss is a big deal.
*
*
* Question: Why is manual splitting good for this workload?
* Answer: Although automated splitting is not a bad option, there are
* benefits to manual splitting.
*
*
* - With growing amounts of data, splits will continually be needed. Since
* you always know exactly what regions you have, long-term debugging and
* profiling is much easier with manual splits. It is hard to trace the logs to
* understand region level problems if it keeps splitting and getting renamed.
*
- Data offlining bugs + unknown number of split regions == oh crap! If an
* WAL or StoreFile was mistakenly unprocessed by HBase due to a weird bug and
* you notice it a day or so later, you can be assured that the regions
* specified in these files are the same as the current regions and you have
* less headaches trying to restore/replay your data.
*
- You can finely tune your compaction algorithm. With roughly uniform data
* growth, it's easy to cause split / compaction storms as the regions all
* roughly hit the same data size at the same time. With manual splits, you can
* let staggered, time-based major compactions spread out your network IO load.
*
*
* Question: What's the optimal number of pre-split regions to create?
* Answer: Mileage will vary depending upon your application.
*
* The short answer for our application is that we started with 10 pre-split
* regions / server and watched our data growth over time. It's better to err on
* the side of too little regions and rolling split later.
*
* The more complicated answer is that this depends upon the largest storefile
* in your region. With a growing data size, this will get larger over time. You
* want the largest region to be just big enough that the
* {@link org.apache.hadoop.hbase.regionserver.HStore} compact
* selection algorithm only compacts it due to a timed major. If you don't, your
* cluster can be prone to compaction storms as the algorithm decides to run
* major compactions on a large series of regions all at once. Note that
* compaction storms are due to the uniform data growth, not the manual split
* decision.
*
* If you pre-split your regions too thin, you can increase the major compaction
* interval by configuring HConstants.MAJOR_COMPACTION_PERIOD. If your data size
* grows too large, use this script to perform a network IO safe rolling split
* of all regions.
*/
@InterfaceAudience.Private
public class RegionSplitter {
private static final Logger LOG = LoggerFactory.getLogger(RegionSplitter.class);
/**
* A generic interface for the RegionSplitter code to use for all it's
* functionality. Note that the original authors of this code use
* {@link HexStringSplit} to partition their table and set it as default, but
* provided this for your custom algorithm. To use, create a new derived class
* from this interface and call {@link RegionSplitter#createPresplitTable} or
* RegionSplitter#rollingSplit(TableName, SplitAlgorithm, Configuration) with the
* argument splitClassName giving the name of your class.
*/
public interface SplitAlgorithm {
/**
* Split a pre-existing region into 2 regions.
*
* @param start
* first row (inclusive)
* @param end
* last row (exclusive)
* @return the split row to use
*/
byte[] split(byte[] start, byte[] end);
/**
* Split an entire table.
*
* @param numRegions
* number of regions to split the table into
*
* @throws RuntimeException
* user input is validated at this time. may throw a runtime
* exception in response to a parse failure
* @return array of split keys for the initial regions of the table. The
* length of the returned array should be numRegions-1.
*/
byte[][] split(int numRegions);
/**
* Some MapReduce jobs may want to run multiple mappers per region,
* this is intended for such usecase.
*
* @param start first row (inclusive)
* @param end last row (exclusive)
* @param numSplits number of splits to generate
* @param inclusive whether start and end are returned as split points
*/
byte[][] split(byte[] start, byte[] end, int numSplits, boolean inclusive);
/**
* In HBase, the first row is represented by an empty byte array. This might
* cause problems with your split algorithm or row printing. All your APIs
* will be passed firstRow() instead of empty array.
*
* @return your representation of your first row
*/
byte[] firstRow();
/**
* In HBase, the last row is represented by an empty byte array. This might
* cause problems with your split algorithm or row printing. All your APIs
* will be passed firstRow() instead of empty array.
*
* @return your representation of your last row
*/
byte[] lastRow();
/**
* In HBase, the last row is represented by an empty byte array. Set this
* value to help the split code understand how to evenly divide the first
* region.
*
* @param userInput
* raw user input (may throw RuntimeException on parse failure)
*/
void setFirstRow(String userInput);
/**
* In HBase, the last row is represented by an empty byte array. Set this
* value to help the split code understand how to evenly divide the last
* region. Note that this last row is inclusive for all rows sharing the
* same prefix.
*
* @param userInput
* raw user input (may throw RuntimeException on parse failure)
*/
void setLastRow(String userInput);
/**
* @param input
* user or file input for row
* @return byte array representation of this row for HBase
*/
byte[] strToRow(String input);
/**
* @param row
* byte array representing a row in HBase
* @return String to use for debug & file printing
*/
String rowToStr(byte[] row);
/**
* @return the separator character to use when storing / printing the row
*/
String separator();
/**
* Set the first row
* @param userInput byte array of the row key.
*/
void setFirstRow(byte[] userInput);
/**
* Set the last row
* @param userInput byte array of the row key.
*/
void setLastRow(byte[] userInput);
}
/**
* The main function for the RegionSplitter application. Common uses:
*
*
* - create a table named 'myTable' with 60 pre-split regions containing 2
* column families 'test' & 'rs', assuming the keys are hex-encoded ASCII:
*
* - bin/hbase org.apache.hadoop.hbase.util.RegionSplitter -c 60 -f test:rs
* myTable HexStringSplit
*
* - create a table named 'myTable' with 50 pre-split regions,
* assuming the keys are decimal-encoded ASCII:
*
* - bin/hbase org.apache.hadoop.hbase.util.RegionSplitter -c 50
* myTable DecimalStringSplit
*
* - perform a rolling split of 'myTable' (i.e. 60 => 120 regions), # 2
* outstanding splits at a time, assuming keys are uniformly distributed
* bytes:
*
* - bin/hbase org.apache.hadoop.hbase.util.RegionSplitter -r -o 2 myTable
* UniformSplit
*
*
*
* There are three SplitAlgorithms built into RegionSplitter, HexStringSplit,
* DecimalStringSplit, and UniformSplit. These are different strategies for
* choosing region boundaries. See their source code for details.
*
* @param args
* Usage: RegionSplitter <TABLE> <SPLITALGORITHM>
* <-c <# regions> -f <family:family:...> | -r
* [-o <# outstanding splits>]>
* [-D <conf.param=value>]
* @throws IOException
* HBase IO problem
* @throws InterruptedException
* user requested exit
* @throws ParseException
* problem parsing user input
*/
@SuppressWarnings("static-access")
public static void main(String[] args) throws IOException,
InterruptedException, ParseException {
Configuration conf = HBaseConfiguration.create();
// parse user input
Options opt = new Options();
opt.addOption(OptionBuilder.withArgName("property=value").hasArg()
.withDescription("Override HBase Configuration Settings").create("D"));
opt.addOption(OptionBuilder.withArgName("region count").hasArg()
.withDescription(
"Create a new table with a pre-split number of regions")
.create("c"));
opt.addOption(OptionBuilder.withArgName("family:family:...").hasArg()
.withDescription(
"Column Families to create with new table. Required with -c")
.create("f"));
opt.addOption("h", false, "Print this usage help");
opt.addOption("r", false, "Perform a rolling split of an existing region");
opt.addOption(OptionBuilder.withArgName("count").hasArg().withDescription(
"Max outstanding splits that have unfinished major compactions")
.create("o"));
opt.addOption(null, "firstrow", true,
"First Row in Table for Split Algorithm");
opt.addOption(null, "lastrow", true,
"Last Row in Table for Split Algorithm");
opt.addOption(null, "risky", false,
"Skip verification steps to complete quickly. "
+ "STRONGLY DISCOURAGED for production systems. ");
CommandLine cmd = new GnuParser().parse(opt, args);
if (cmd.hasOption("D")) {
for (String confOpt : cmd.getOptionValues("D")) {
String[] kv = confOpt.split("=", 2);
if (kv.length == 2) {
conf.set(kv[0], kv[1]);
LOG.debug("-D configuration override: " + kv[0] + "=" + kv[1]);
} else {
throw new ParseException("-D option format invalid: " + confOpt);
}
}
}
if (cmd.hasOption("risky")) {
conf.setBoolean("split.verify", false);
}
boolean createTable = cmd.hasOption("c") && cmd.hasOption("f");
boolean rollingSplit = cmd.hasOption("r");
boolean oneOperOnly = createTable ^ rollingSplit;
if (2 != cmd.getArgList().size() || !oneOperOnly || cmd.hasOption("h")) {
new HelpFormatter().printHelp("bin/hbase regionsplitter \n"+
"SPLITALGORITHM is the java class name of a class implementing " +
"SplitAlgorithm, or one of the special strings HexStringSplit or " +
"DecimalStringSplit or UniformSplit, which are built-in split algorithms. " +
"HexStringSplit treats keys as hexadecimal ASCII, and " +
"DecimalStringSplit treats keys as decimal ASCII, and " +
"UniformSplit treats keys as arbitrary bytes.", opt);
return;
}
TableName tableName = TableName.valueOf(cmd.getArgs()[0]);
String splitClass = cmd.getArgs()[1];
SplitAlgorithm splitAlgo = newSplitAlgoInstance(conf, splitClass);
if (cmd.hasOption("firstrow")) {
splitAlgo.setFirstRow(cmd.getOptionValue("firstrow"));
}
if (cmd.hasOption("lastrow")) {
splitAlgo.setLastRow(cmd.getOptionValue("lastrow"));
}
if (createTable) {
conf.set("split.count", cmd.getOptionValue("c"));
createPresplitTable(tableName, splitAlgo, cmd.getOptionValue("f").split(":"), conf);
}
if (rollingSplit) {
if (cmd.hasOption("o")) {
conf.set("split.outstanding", cmd.getOptionValue("o"));
}
rollingSplit(tableName, splitAlgo, conf);
}
}
static void createPresplitTable(TableName tableName, SplitAlgorithm splitAlgo,
String[] columnFamilies, Configuration conf)
throws IOException, InterruptedException {
final int splitCount = conf.getInt("split.count", 0);
Preconditions.checkArgument(splitCount > 1, "Split count must be > 1");
Preconditions.checkArgument(columnFamilies.length > 0,
"Must specify at least one column family. ");
LOG.debug("Creating table " + tableName + " with " + columnFamilies.length
+ " column families. Presplitting to " + splitCount + " regions");
TableDescriptorBuilder builder = TableDescriptorBuilder.newBuilder(tableName);
for (String cf : columnFamilies) {
builder.setColumnFamily(ColumnFamilyDescriptorBuilder.of(cf));
}
try (Connection connection = ConnectionFactory.createConnection(conf)) {
Admin admin = connection.getAdmin();
try {
Preconditions.checkArgument(!admin.tableExists(tableName),
"Table already exists: " + tableName);
admin.createTable(builder.build(), splitAlgo.split(splitCount));
} finally {
admin.close();
}
LOG.debug("Table created! Waiting for regions to show online in META...");
if (!conf.getBoolean("split.verify", true)) {
// NOTE: createTable is synchronous on the table, but not on the regions
int onlineRegions = 0;
while (onlineRegions < splitCount) {
onlineRegions = MetaTableAccessor.getRegionCount(connection, tableName);
LOG.debug(onlineRegions + " of " + splitCount + " regions online...");
if (onlineRegions < splitCount) {
Thread.sleep(10 * 1000); // sleep
}
}
}
LOG.debug("Finished creating table with " + splitCount + " regions");
}
}
/**
* Alternative getCurrentNrHRS which is no longer available.
* @param connection
* @return Rough count of regionservers out on cluster.
* @throws IOException if a remote or network exception occurs
*/
private static int getRegionServerCount(final Connection connection) throws IOException {
try (Admin admin = connection.getAdmin()) {
Collection servers = admin.getRegionServers();
return servers == null || servers.isEmpty()? 0: servers.size();
}
}
private static byte [] readFile(final FileSystem fs, final Path path) throws IOException {
FSDataInputStream tmpIn = fs.open(path);
try {
byte [] rawData = new byte[tmpIn.available()];
tmpIn.readFully(rawData);
return rawData;
} finally {
tmpIn.close();
}
}
static void rollingSplit(TableName tableName, SplitAlgorithm splitAlgo, Configuration conf)
throws IOException, InterruptedException {
final int minOS = conf.getInt("split.outstanding", 2);
try (Connection connection = ConnectionFactory.createConnection(conf)) {
// Max outstanding splits. default == 50% of servers
final int MAX_OUTSTANDING = Math.max(getRegionServerCount(connection) / 2, minOS);
Path hbDir = FSUtils.getRootDir(conf);
Path tableDir = FSUtils.getTableDir(hbDir, tableName);
Path splitFile = new Path(tableDir, "_balancedSplit");
FileSystem fs = FileSystem.get(conf);
// Get a list of daughter regions to create
LinkedList> tmpRegionSet = null;
try (Table table = connection.getTable(tableName)) {
tmpRegionSet = getSplits(connection, tableName, splitAlgo);
}
LinkedList> outstanding = Lists.newLinkedList();
int splitCount = 0;
final int origCount = tmpRegionSet.size();
// all splits must compact & we have 1 compact thread, so 2 split
// requests to the same RS can stall the outstanding split queue.
// To fix, group the regions into an RS pool and round-robin through it
LOG.debug("Bucketing regions by regionserver...");
TreeMap>> daughterRegions =
Maps.newTreeMap();
// Get a regionLocator. Need it in below.
try (RegionLocator regionLocator = connection.getRegionLocator(tableName)) {
for (Pair dr : tmpRegionSet) {
ServerName rsLocation = regionLocator.getRegionLocation(dr.getSecond()).getServerName();
if (!daughterRegions.containsKey(rsLocation)) {
LinkedList> entry = Lists.newLinkedList();
daughterRegions.put(rsLocation, entry);
}
daughterRegions.get(rsLocation).add(dr);
}
LOG.debug("Done with bucketing. Split time!");
long startTime = System.currentTimeMillis();
// Open the split file and modify it as splits finish
byte[] rawData = readFile(fs, splitFile);
FSDataOutputStream splitOut = fs.create(splitFile);
try {
splitOut.write(rawData);
try {
// *** split code ***
while (!daughterRegions.isEmpty()) {
LOG.debug(daughterRegions.size() + " RS have regions to splt.");
// Get ServerName to region count mapping
final TreeMap rsSizes = Maps.newTreeMap();
List hrls = regionLocator.getAllRegionLocations();
for (HRegionLocation hrl: hrls) {
ServerName sn = hrl.getServerName();
if (rsSizes.containsKey(sn)) {
rsSizes.put(sn, rsSizes.get(sn) + 1);
} else {
rsSizes.put(sn, 1);
}
}
// Round-robin through the ServerName list. Choose the lightest-loaded servers
// first to keep the master from load-balancing regions as we split.
for (Map.Entry>> daughterRegion :
daughterRegions.entrySet()) {
Pair dr = null;
ServerName rsLoc = daughterRegion.getKey();
LinkedList> regionList = daughterRegion.getValue();
// Find a region in the ServerName list that hasn't been moved
LOG.debug("Finding a region on " + rsLoc);
while (!regionList.isEmpty()) {
dr = regionList.pop();
// get current region info
byte[] split = dr.getSecond();
HRegionLocation regionLoc = regionLocator.getRegionLocation(split);
// if this region moved locations
ServerName newRs = regionLoc.getServerName();
if (newRs.compareTo(rsLoc) != 0) {
LOG.debug("Region with " + splitAlgo.rowToStr(split)
+ " moved to " + newRs + ". Relocating...");
// relocate it, don't use it right now
if (!daughterRegions.containsKey(newRs)) {
LinkedList> entry = Lists.newLinkedList();
daughterRegions.put(newRs, entry);
}
daughterRegions.get(newRs).add(dr);
dr = null;
continue;
}
// make sure this region wasn't already split
byte[] sk = regionLoc.getRegionInfo().getStartKey();
if (sk.length != 0) {
if (Bytes.equals(split, sk)) {
LOG.debug("Region already split on "
+ splitAlgo.rowToStr(split) + ". Skipping this region...");
++splitCount;
dr = null;
continue;
}
byte[] start = dr.getFirst();
Preconditions.checkArgument(Bytes.equals(start, sk), splitAlgo
.rowToStr(start) + " != " + splitAlgo.rowToStr(sk));
}
// passed all checks! found a good region
break;
}
if (regionList.isEmpty()) {
daughterRegions.remove(rsLoc);
}
if (dr == null)
continue;
// we have a good region, time to split!
byte[] split = dr.getSecond();
LOG.debug("Splitting at " + splitAlgo.rowToStr(split));
try (Admin admin = connection.getAdmin()) {
admin.split(tableName, split);
}
LinkedList> finished = Lists.newLinkedList();
LinkedList> local_finished = Lists.newLinkedList();
if (conf.getBoolean("split.verify", true)) {
// we need to verify and rate-limit our splits
outstanding.addLast(dr);
// with too many outstanding splits, wait for some to finish
while (outstanding.size() >= MAX_OUTSTANDING) {
LOG.debug("Wait for outstanding splits " + outstanding.size());
local_finished = splitScan(outstanding, connection, tableName, splitAlgo);
if (local_finished.isEmpty()) {
Thread.sleep(30 * 1000);
} else {
finished.addAll(local_finished);
outstanding.removeAll(local_finished);
LOG.debug(local_finished.size() + " outstanding splits finished");
}
}
} else {
finished.add(dr);
}
// mark each finished region as successfully split.
for (Pair region : finished) {
splitOut.writeChars("- " + splitAlgo.rowToStr(region.getFirst())
+ " " + splitAlgo.rowToStr(region.getSecond()) + "\n");
splitCount++;
if (splitCount % 10 == 0) {
long tDiff = (System.currentTimeMillis() - startTime)
/ splitCount;
LOG.debug("STATUS UPDATE: " + splitCount + " / " + origCount
+ ". Avg Time / Split = "
+ org.apache.hadoop.util.StringUtils.formatTime(tDiff));
}
}
}
}
if (conf.getBoolean("split.verify", true)) {
while (!outstanding.isEmpty()) {
LOG.debug("Finally Wait for outstanding splits " + outstanding.size());
LinkedList> finished = splitScan(outstanding,
connection, tableName, splitAlgo);
if (finished.isEmpty()) {
Thread.sleep(30 * 1000);
} else {
outstanding.removeAll(finished);
for (Pair region : finished) {
splitOut.writeChars("- " + splitAlgo.rowToStr(region.getFirst())
+ " " + splitAlgo.rowToStr(region.getSecond()) + "\n");
splitCount++;
}
LOG.debug("Finally " + finished.size() + " outstanding splits finished");
}
}
}
LOG.debug("All regions have been successfully split!");
} finally {
long tDiff = System.currentTimeMillis() - startTime;
LOG.debug("TOTAL TIME = "
+ org.apache.hadoop.util.StringUtils.formatTime(tDiff));
LOG.debug("Splits = " + splitCount);
if (0 < splitCount) {
LOG.debug("Avg Time / Split = "
+ org.apache.hadoop.util.StringUtils.formatTime(tDiff / splitCount));
}
}
} finally {
splitOut.close();
fs.delete(splitFile, false);
}
}
}
}
/**
* @throws IOException if the specified SplitAlgorithm class couldn't be
* instantiated
*/
public static SplitAlgorithm newSplitAlgoInstance(Configuration conf,
String splitClassName) throws IOException {
Class splitClass;
// For split algorithms builtin to RegionSplitter, the user can specify
// their simple class name instead of a fully qualified class name.
if(splitClassName.equals(HexStringSplit.class.getSimpleName())) {
splitClass = HexStringSplit.class;
} else if (splitClassName.equals(DecimalStringSplit.class.getSimpleName())) {
splitClass = DecimalStringSplit.class;
} else if (splitClassName.equals(UniformSplit.class.getSimpleName())) {
splitClass = UniformSplit.class;
} else {
try {
splitClass = conf.getClassByName(splitClassName);
} catch (ClassNotFoundException e) {
throw new IOException("Couldn't load split class " + splitClassName, e);
}
if(splitClass == null) {
throw new IOException("Failed loading split class " + splitClassName);
}
if(!SplitAlgorithm.class.isAssignableFrom(splitClass)) {
throw new IOException(
"Specified split class doesn't implement SplitAlgorithm");
}
}
try {
return splitClass.asSubclass(SplitAlgorithm.class).getDeclaredConstructor().newInstance();
} catch (Exception e) {
throw new IOException("Problem loading split algorithm: ", e);
}
}
static LinkedList> splitScan(
LinkedList> regionList,
final Connection connection,
final TableName tableName,
SplitAlgorithm splitAlgo)
throws IOException, InterruptedException {
LinkedList> finished = Lists.newLinkedList();
LinkedList> logicalSplitting = Lists.newLinkedList();
LinkedList> physicalSplitting = Lists.newLinkedList();
// Get table info
Pair tableDirAndSplitFile =
getTableDirAndSplitFile(connection.getConfiguration(), tableName);
Path tableDir = tableDirAndSplitFile.getFirst();
FileSystem fs = tableDir.getFileSystem(connection.getConfiguration());
// Clear the cache to forcibly refresh region information
((ClusterConnection)connection).clearRegionLocationCache();
TableDescriptor htd = null;
try (Table table = connection.getTable(tableName)) {
htd = table.getDescriptor();
}
try (RegionLocator regionLocator = connection.getRegionLocator(tableName)) {
// for every region that hasn't been verified as a finished split
for (Pair region : regionList) {
byte[] start = region.getFirst();
byte[] split = region.getSecond();
// see if the new split daughter region has come online
try {
HRegionInfo dri = regionLocator.getRegionLocation(split).getRegionInfo();
if (dri.isOffline() || !Bytes.equals(dri.getStartKey(), split)) {
logicalSplitting.add(region);
continue;
}
} catch (NoServerForRegionException nsfre) {
// NSFRE will occur if the old hbase:meta entry has no server assigned
LOG.info(nsfre.toString(), nsfre);
logicalSplitting.add(region);
continue;
}
try {
// when a daughter region is opened, a compaction is triggered
// wait until compaction completes for both daughter regions
LinkedList check = Lists.newLinkedList();
check.add(regionLocator.getRegionLocation(start).getRegionInfo());
check.add(regionLocator.getRegionLocation(split).getRegionInfo());
for (HRegionInfo hri : check.toArray(new HRegionInfo[check.size()])) {
byte[] sk = hri.getStartKey();
if (sk.length == 0)
sk = splitAlgo.firstRow();
HRegionFileSystem regionFs = HRegionFileSystem.openRegionFromFileSystem(
connection.getConfiguration(), fs, tableDir, hri, true);
// Check every Column Family for that region -- check does not have references.
boolean refFound = false;
for (ColumnFamilyDescriptor c : htd.getColumnFamilies()) {
if ((refFound = regionFs.hasReferences(c.getNameAsString()))) {
break;
}
}
// compaction is completed when all reference files are gone
if (!refFound) {
check.remove(hri);
}
}
if (check.isEmpty()) {
finished.add(region);
} else {
physicalSplitting.add(region);
}
} catch (NoServerForRegionException nsfre) {
LOG.debug("No Server Exception thrown for: " + splitAlgo.rowToStr(start));
physicalSplitting.add(region);
((ClusterConnection)connection).clearRegionLocationCache();
}
}
LOG.debug("Split Scan: " + finished.size() + " finished / "
+ logicalSplitting.size() + " split wait / "
+ physicalSplitting.size() + " reference wait");
return finished;
}
}
/**
* @param conf
* @param tableName
* @return A Pair where first item is table dir and second is the split file.
* @throws IOException if a remote or network exception occurs
*/
private static Pair getTableDirAndSplitFile(final Configuration conf,
final TableName tableName)
throws IOException {
Path hbDir = FSUtils.getRootDir(conf);
Path tableDir = FSUtils.getTableDir(hbDir, tableName);
Path splitFile = new Path(tableDir, "_balancedSplit");
return new Pair<>(tableDir, splitFile);
}
static LinkedList> getSplits(final Connection connection,
TableName tableName, SplitAlgorithm splitAlgo)
throws IOException {
Pair tableDirAndSplitFile =
getTableDirAndSplitFile(connection.getConfiguration(), tableName);
Path tableDir = tableDirAndSplitFile.getFirst();
Path splitFile = tableDirAndSplitFile.getSecond();
FileSystem fs = tableDir.getFileSystem(connection.getConfiguration());
// Using strings because (new byte[]{0}).equals(new byte[]{0}) == false
Set> daughterRegions = Sets.newHashSet();
// Does a split file exist?
if (!fs.exists(splitFile)) {
// NO = fresh start. calculate splits to make
LOG.debug("No " + splitFile.getName() + " file. Calculating splits ");
// Query meta for all regions in the table
Set> rows = Sets.newHashSet();
Pair tmp = null;
try (RegionLocator regionLocator = connection.getRegionLocator(tableName)) {
tmp = regionLocator.getStartEndKeys();
}
Preconditions.checkArgument(tmp.getFirst().length == tmp.getSecond().length,
"Start and End rows should be equivalent");
for (int i = 0; i < tmp.getFirst().length; ++i) {
byte[] start = tmp.getFirst()[i], end = tmp.getSecond()[i];
if (start.length == 0)
start = splitAlgo.firstRow();
if (end.length == 0)
end = splitAlgo.lastRow();
rows.add(Pair.newPair(start, end));
}
LOG.debug("Table " + tableName + " has " + rows.size() + " regions that will be split.");
// prepare the split file
Path tmpFile = new Path(tableDir, "_balancedSplit_prepare");
FSDataOutputStream tmpOut = fs.create(tmpFile);
// calculate all the splits == [daughterRegions] = [(start, splitPoint)]
for (Pair r : rows) {
byte[] splitPoint = splitAlgo.split(r.getFirst(), r.getSecond());
String startStr = splitAlgo.rowToStr(r.getFirst());
String splitStr = splitAlgo.rowToStr(splitPoint);
daughterRegions.add(Pair.newPair(startStr, splitStr));
LOG.debug("Will Split [" + startStr + " , "
+ splitAlgo.rowToStr(r.getSecond()) + ") at " + splitStr);
tmpOut.writeChars("+ " + startStr + splitAlgo.separator() + splitStr
+ "\n");
}
tmpOut.close();
fs.rename(tmpFile, splitFile);
} else {
LOG.debug("_balancedSplit file found. Replay log to restore state...");
FSUtils.getInstance(fs, connection.getConfiguration())
.recoverFileLease(fs, splitFile, connection.getConfiguration(), null);
// parse split file and process remaining splits
FSDataInputStream tmpIn = fs.open(splitFile);
StringBuilder sb = new StringBuilder(tmpIn.available());
while (tmpIn.available() > 0) {
sb.append(tmpIn.readChar());
}
tmpIn.close();
for (String line : sb.toString().split("\n")) {
String[] cmd = line.split(splitAlgo.separator());
Preconditions.checkArgument(3 == cmd.length);
byte[] start = splitAlgo.strToRow(cmd[1]);
String startStr = splitAlgo.rowToStr(start);
byte[] splitPoint = splitAlgo.strToRow(cmd[2]);
String splitStr = splitAlgo.rowToStr(splitPoint);
Pair r = Pair.newPair(startStr, splitStr);
if (cmd[0].equals("+")) {
LOG.debug("Adding: " + r);
daughterRegions.add(r);
} else {
LOG.debug("Removing: " + r);
Preconditions.checkArgument(cmd[0].equals("-"),
"Unknown option: " + cmd[0]);
Preconditions.checkState(daughterRegions.contains(r),
"Missing row: " + r);
daughterRegions.remove(r);
}
}
LOG.debug("Done reading. " + daughterRegions.size() + " regions left.");
}
LinkedList> ret = Lists.newLinkedList();
for (Pair r : daughterRegions) {
ret.add(Pair.newPair(splitAlgo.strToRow(r.getFirst()), splitAlgo
.strToRow(r.getSecond())));
}
return ret;
}
/**
* HexStringSplit is a well-known {@link SplitAlgorithm} for choosing region
* boundaries. The format of a HexStringSplit region boundary is the ASCII
* representation of an MD5 checksum, or any other uniformly distributed
* hexadecimal value. Row are hex-encoded long values in the range
* "00000000" => "FFFFFFFF" and are left-padded with zeros to keep the
* same order lexicographically as if they were binary.
*
* Since this split algorithm uses hex strings as keys, it is easy to read &
* write in the shell but takes up more space and may be non-intuitive.
*/
public static class HexStringSplit extends NumberStringSplit {
final static String DEFAULT_MIN_HEX = "00000000";
final static String DEFAULT_MAX_HEX = "FFFFFFFF";
final static int RADIX_HEX = 16;
public HexStringSplit() {
super(DEFAULT_MIN_HEX, DEFAULT_MAX_HEX, RADIX_HEX);
}
}
/**
* The format of a DecimalStringSplit region boundary is the ASCII representation of
* reversed sequential number, or any other uniformly distributed decimal value.
* Row are decimal-encoded long values in the range
* "00000000" => "99999999" and are left-padded with zeros to keep the
* same order lexicographically as if they were binary.
*/
public static class DecimalStringSplit extends NumberStringSplit {
final static String DEFAULT_MIN_DEC = "00000000";
final static String DEFAULT_MAX_DEC = "99999999";
final static int RADIX_DEC = 10;
public DecimalStringSplit() {
super(DEFAULT_MIN_DEC, DEFAULT_MAX_DEC, RADIX_DEC);
}
}
public abstract static class NumberStringSplit implements SplitAlgorithm {
String firstRow;
BigInteger firstRowInt;
String lastRow;
BigInteger lastRowInt;
int rowComparisonLength;
int radix;
NumberStringSplit(String minRow, String maxRow, int radix) {
this.firstRow = minRow;
this.lastRow = maxRow;
this.radix = radix;
this.firstRowInt = BigInteger.ZERO;
this.lastRowInt = new BigInteger(lastRow, this.radix);
this.rowComparisonLength = lastRow.length();
}
@Override
public byte[] split(byte[] start, byte[] end) {
BigInteger s = convertToBigInteger(start);
BigInteger e = convertToBigInteger(end);
Preconditions.checkArgument(!e.equals(BigInteger.ZERO));
return convertToByte(split2(s, e));
}
@Override
public byte[][] split(int n) {
Preconditions.checkArgument(lastRowInt.compareTo(firstRowInt) > 0,
"last row (%s) is configured less than first row (%s)", lastRow,
firstRow);
// +1 to range because the last row is inclusive
BigInteger range = lastRowInt.subtract(firstRowInt).add(BigInteger.ONE);
Preconditions.checkState(range.compareTo(BigInteger.valueOf(n)) >= 0,
"split granularity (%s) is greater than the range (%s)", n, range);
BigInteger[] splits = new BigInteger[n - 1];
BigInteger sizeOfEachSplit = range.divide(BigInteger.valueOf(n));
for (int i = 1; i < n; i++) {
// NOTE: this means the last region gets all the slop.
// This is not a big deal if we're assuming n << MAXHEX
splits[i - 1] = firstRowInt.add(sizeOfEachSplit.multiply(BigInteger
.valueOf(i)));
}
return convertToBytes(splits);
}
@Override
public byte[][] split(byte[] start, byte[] end, int numSplits, boolean inclusive) {
BigInteger s = convertToBigInteger(start);
BigInteger e = convertToBigInteger(end);
Preconditions.checkArgument(e.compareTo(s) > 0,
"last row (%s) is configured less than first row (%s)", rowToStr(end),
end);
// +1 to range because the last row is inclusive
BigInteger range = e.subtract(s).add(BigInteger.ONE);
Preconditions.checkState(range.compareTo(BigInteger.valueOf(numSplits)) >= 0,
"split granularity (%s) is greater than the range (%s)", numSplits, range);
BigInteger[] splits = new BigInteger[numSplits - 1];
BigInteger sizeOfEachSplit = range.divide(BigInteger.valueOf(numSplits));
for (int i = 1; i < numSplits; i++) {
// NOTE: this means the last region gets all the slop.
// This is not a big deal if we're assuming n << MAXHEX
splits[i - 1] = s.add(sizeOfEachSplit.multiply(BigInteger
.valueOf(i)));
}
if (inclusive) {
BigInteger[] inclusiveSplitPoints = new BigInteger[numSplits + 1];
inclusiveSplitPoints[0] = convertToBigInteger(start);
inclusiveSplitPoints[numSplits] = convertToBigInteger(end);
System.arraycopy(splits, 0, inclusiveSplitPoints, 1, splits.length);
return convertToBytes(inclusiveSplitPoints);
} else {
return convertToBytes(splits);
}
}
@Override
public byte[] firstRow() {
return convertToByte(firstRowInt);
}
@Override
public byte[] lastRow() {
return convertToByte(lastRowInt);
}
@Override
public void setFirstRow(String userInput) {
firstRow = userInput;
firstRowInt = new BigInteger(firstRow, radix);
}
@Override
public void setLastRow(String userInput) {
lastRow = userInput;
lastRowInt = new BigInteger(lastRow, radix);
// Precondition: lastRow > firstRow, so last's length is the greater
rowComparisonLength = lastRow.length();
}
@Override
public byte[] strToRow(String in) {
return convertToByte(new BigInteger(in, radix));
}
@Override
public String rowToStr(byte[] row) {
return Bytes.toStringBinary(row);
}
@Override
public String separator() {
return " ";
}
@Override
public void setFirstRow(byte[] userInput) {
firstRow = Bytes.toString(userInput);
}
@Override
public void setLastRow(byte[] userInput) {
lastRow = Bytes.toString(userInput);
}
/**
* Divide 2 numbers in half (for split algorithm)
*
* @param a number #1
* @param b number #2
* @return the midpoint of the 2 numbers
*/
public BigInteger split2(BigInteger a, BigInteger b) {
return a.add(b).divide(BigInteger.valueOf(2)).abs();
}
/**
* Returns an array of bytes corresponding to an array of BigIntegers
*
* @param bigIntegers numbers to convert
* @return bytes corresponding to the bigIntegers
*/
public byte[][] convertToBytes(BigInteger[] bigIntegers) {
byte[][] returnBytes = new byte[bigIntegers.length][];
for (int i = 0; i < bigIntegers.length; i++) {
returnBytes[i] = convertToByte(bigIntegers[i]);
}
return returnBytes;
}
/**
* Returns the bytes corresponding to the BigInteger
*
* @param bigInteger number to convert
* @param pad padding length
* @return byte corresponding to input BigInteger
*/
public byte[] convertToByte(BigInteger bigInteger, int pad) {
String bigIntegerString = bigInteger.toString(radix);
bigIntegerString = StringUtils.leftPad(bigIntegerString, pad, '0');
return Bytes.toBytes(bigIntegerString);
}
/**
* Returns the bytes corresponding to the BigInteger
*
* @param bigInteger number to convert
* @return corresponding bytes
*/
public byte[] convertToByte(BigInteger bigInteger) {
return convertToByte(bigInteger, rowComparisonLength);
}
/**
* Returns the BigInteger represented by the byte array
*
* @param row byte array representing row
* @return the corresponding BigInteger
*/
public BigInteger convertToBigInteger(byte[] row) {
return (row.length > 0) ? new BigInteger(Bytes.toString(row), radix)
: BigInteger.ZERO;
}
@Override
public String toString() {
return this.getClass().getSimpleName() + " [" + rowToStr(firstRow())
+ "," + rowToStr(lastRow()) + "]";
}
}
/**
* A SplitAlgorithm that divides the space of possible keys evenly. Useful
* when the keys are approximately uniform random bytes (e.g. hashes). Rows
* are raw byte values in the range 00 => FF and are right-padded with
* zeros to keep the same memcmp() order. This is the natural algorithm to use
* for a byte[] environment and saves space, but is not necessarily the
* easiest for readability.
*/
public static class UniformSplit implements SplitAlgorithm {
static final byte xFF = (byte) 0xFF;
byte[] firstRowBytes = ArrayUtils.EMPTY_BYTE_ARRAY;
byte[] lastRowBytes =
new byte[] {xFF, xFF, xFF, xFF, xFF, xFF, xFF, xFF};
@Override
public byte[] split(byte[] start, byte[] end) {
return Bytes.split(start, end, 1)[1];
}
@Override
public byte[][] split(int numRegions) {
Preconditions.checkArgument(
Bytes.compareTo(lastRowBytes, firstRowBytes) > 0,
"last row (%s) is configured less than first row (%s)",
Bytes.toStringBinary(lastRowBytes),
Bytes.toStringBinary(firstRowBytes));
byte[][] splits = Bytes.split(firstRowBytes, lastRowBytes, true,
numRegions - 1);
Preconditions.checkState(splits != null,
"Could not split region with given user input: " + this);
// remove endpoints, which are included in the splits list
return splits == null? null: Arrays.copyOfRange(splits, 1, splits.length - 1);
}
@Override
public byte[][] split(byte[] start, byte[] end, int numSplits, boolean inclusive) {
if (Arrays.equals(start, HConstants.EMPTY_BYTE_ARRAY)) {
start = firstRowBytes;
}
if (Arrays.equals(end, HConstants.EMPTY_BYTE_ARRAY)) {
end = lastRowBytes;
}
Preconditions.checkArgument(
Bytes.compareTo(end, start) > 0,
"last row (%s) is configured less than first row (%s)",
Bytes.toStringBinary(end),
Bytes.toStringBinary(start));
byte[][] splits = Bytes.split(start, end, true,
numSplits - 1);
Preconditions.checkState(splits != null,
"Could not calculate input splits with given user input: " + this);
if (inclusive) {
return splits;
} else {
// remove endpoints, which are included in the splits list
return Arrays.copyOfRange(splits, 1, splits.length - 1);
}
}
@Override
public byte[] firstRow() {
return firstRowBytes;
}
@Override
public byte[] lastRow() {
return lastRowBytes;
}
@Override
public void setFirstRow(String userInput) {
firstRowBytes = Bytes.toBytesBinary(userInput);
}
@Override
public void setLastRow(String userInput) {
lastRowBytes = Bytes.toBytesBinary(userInput);
}
@Override
public void setFirstRow(byte[] userInput) {
firstRowBytes = userInput;
}
@Override
public void setLastRow(byte[] userInput) {
lastRowBytes = userInput;
}
@Override
public byte[] strToRow(String input) {
return Bytes.toBytesBinary(input);
}
@Override
public String rowToStr(byte[] row) {
return Bytes.toStringBinary(row);
}
@Override
public String separator() {
return ",";
}
@Override
public String toString() {
return this.getClass().getSimpleName() + " [" + rowToStr(firstRow())
+ "," + rowToStr(lastRow()) + "]";
}
}
}
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