Hadoop学习之路（十）HDFS API的使用
HDFS API的高级编程
HDFS的API就两个：FileSystem 和Configuration
1、文件的上传和下载
package com.ghgj.hdfs.api; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path; public class HDFS_GET_AND_PUT { public static void main(String[] args) throws Exception { Configuration conf = new Configuration();
conf.set("fs.defaultFS", "hdfs://hadoop1:9000");
conf.set("dfs.replication", "2");
FileSystem fs = FileSystem.get(conf); /**
* 更改操作用户有两种方式:
*
* 1、直接设置运行换种的用户名为hadoop
*
* VM arguments ; -DHADOOP_USER_NAME=hadoop
*
* 2、在代码中进行声明
*
* System.setProperty("HADOOP_USER_NAME", "hadoop");
*/
System.setProperty("HADOOP_USER_NAME", "hadoop"); // 上传
fs.copyFromLocalFile(new Path("c:/sss.txt"), new Path("/a/ggg.txt")); /**
* .crc ： 校验文件
*
* 每个块的元数据信息都只会记录合法数据的起始偏移量： qqq.txt blk_41838 : 0 - 1100byte
*
* 如果进行非法的数据追加。最终是能够下载合法数据。
* 由于你在数据的中间， 也就是说在 0 -1100 之间的范围进行了数据信息的更改。 造成了采用CRC算法计算出来校验值，和最初存入进HDFS的校验值
* 不一致。HDFS就认为当前这个文件被损坏了。
*/ // 下载
fs.copyToLocalFile(new Path("/a/qqq.txt"), new Path("c:/qqq3.txt")); /**
* 上传和下载的API的底层封装其实就是 ： FileUtil.copy(....)
*/ fs.close();
}
}
2、配置文件conf
package com.exam.hdfs; import java.io.IOException;
import java.util.Iterator;
import java.util.Map.Entry; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem; public class TestConf1 { public static void main(String[] args) throws Exception { /**
* 底层会加载一堆的配置文件：
*
* core-default.xml
* hdfs-default.xml
* mapred-default.xml
* yarn-default.xml
*/
Configuration conf = new Configuration();
// conf.addResource("hdfs-default.xml"); /**
* 当前这个hdfs-site.xml文件就放置在这个项目中的src下。也就是classpath路径下。
* 所以 FS在初始化的时候，会把hdfs-site.xml这个文件中的name-value对解析到conf中
*
*
* 但是：
*
* 1、如果hdfs-site.xml 不在src下， 看是否能加载？？？ 不能
*
* 2、如果文件名不叫做 hdfs-default.xml 或者 hdsf-site.xml 看是否能自动加载？？？ 不能
*
* 得出的结论：
*
* 如果需要项目代码自动加载配置文件中的信息，那么就必须把配置文件改成-default.xml或者-site.xml的名称
* 而且必须放置在src下
*
* 那如果不叫这个名，或者不在src下，也需要加载这些配置文件中的参数：
*
* 必须使用conf对象提供的一些方法去手动加载
*/
// conf.addResource("hdfs-site.xml");
conf.set("dfs.replication", "1");
conf.addResource("myconfig/hdfs-site.xml"); /**
* 依次加载的参数信息的顺序是：
*
* 1、加载 core/hdfs/mapred/yarn-default.xml
*
* 2、加载通过conf.addResources()加载的配置文件
*
* 3、加载conf.set(name, value)
*/ FileSystem fs = FileSystem.get(conf); System.out.println(conf.get("dfs.replication")); Iterator<Entry<String, String>> iterator = conf.iterator();
while(iterator.hasNext()){
Entry<String, String> e = iterator.next();
System.out.println(e.getKey() + "\t" + e.getValue());
}
}
}
输出结果
log4j:WARN No appenders could be found for logger (org.apache.hadoop.metrics2.lib.MutableMetricsFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
1
hadoop.security.groups.cache.secs 300
dfs.datanode.cache.revocation.timeout.ms 900000
dfs.namenode.resource.check.interval 5000
s3.client-write-packet-size 65536
dfs.client.https.need-auth false
dfs.replication 1
hadoop.security.group.mapping.ldap.directory.search.timeout 10000
dfs.datanode.available-space-volume-choosing-policy.balanced-space-threshold 10737418240
hadoop.work.around.non.threadsafe.getpwuid false
dfs.namenode.write-lock-reporting-threshold-ms 5000
fs.ftp.host.port 21
dfs.namenode.avoid.read.stale.datanode false
dfs.journalnode.rpc-address 0.0.0.0:8485
hadoop.security.kms.client.encrypted.key.cache.expiry 43200000
ipc.client.connection.maxidletime 10000
hadoop.registry.zk.session.timeout.ms 60000
tfile.io.chunk.size 1048576
fs.automatic.close true
ha.health-monitor.sleep-after-disconnect.ms 1000
io.map.index.interval 128
dfs.namenode.https-address 0.0.0.0:50470
dfs.mover.max-no-move-interval 60000
io.seqfile.sorter.recordlimit 1000000
fs.s3n.multipart.uploads.enabled false
hadoop.util.hash.type murmur
dfs.namenode.replication.min 1
dfs.datanode.directoryscan.threads 1
dfs.namenode.fs-limits.min-block-size 1048576
dfs.datanode.directoryscan.interval 21600
fs.AbstractFileSystem.file.impl org.apache.hadoop.fs.local.LocalFs
dfs.namenode.acls.enabled false
dfs.client.short.circuit.replica.stale.threshold.ms 1800000
net.topology.script.number.args 100
hadoop.http.authentication.token.validity 36000
fs.s3.block.size 67108864
dfs.namenode.resource.du.reserved 104857600
ha.failover-controller.graceful-fence.rpc-timeout.ms 5000
s3native.bytes-per-checksum 512
dfs.namenode.datanode.registration.ip-hostname-check true
dfs.namenode.path.based.cache.block.map.allocation.percent 0.25
dfs.namenode.backup.http-address 0.0.0.0:50105
hadoop.security.group.mapping org.apache.hadoop.security.JniBasedUnixGroupsMappingWithFallback
dfs.namenode.edits.noeditlogchannelflush false
dfs.datanode.cache.revocation.polling.ms 500
dfs.namenode.audit.loggers default
hadoop.security.groups.cache.warn.after.ms 5000
io.serializations org.apache.hadoop.io.serializer.WritableSerialization,org.apache.hadoop.io.serializer.avro.AvroSpecificSerialization,org.apache.hadoop.io.serializer.avro.AvroReflectSerialization
dfs.namenode.lazypersist.file.scrub.interval.sec 300
fs.s3a.threads.core 15
hadoop.security.crypto.buffer.size 8192
hadoop.http.cross-origin.allowed-methods GET,POST,HEAD
hadoop.registry.zk.retry.interval.ms 1000
dfs.http.policy HTTP_ONLY
hadoop.registry.secure false
dfs.namenode.replication.interval 3
dfs.namenode.safemode.min.datanodes 0
dfs.client.file-block-storage-locations.num-threads 10
nfs.dump.dir /tmp/.hdfs-nfs
dfs.namenode.secondary.https-address 0.0.0.0:50091
hadoop.kerberos.kinit.command kinit
dfs.block.access.token.lifetime 600
dfs.webhdfs.enabled true
dfs.client.use.datanode.hostname false
dfs.namenode.delegation.token.max-lifetime 604800000
fs.trash.interval 0
dfs.datanode.drop.cache.behind.writes false
dfs.namenode.avoid.write.stale.datanode false
dfs.namenode.num.extra.edits.retained 1000000
s3.blocksize 67108864
ipc.client.connect.max.retries.on.timeouts 45
dfs.datanode.data.dir /home/hadoop/data/hadoopdata/data
fs.s3.buffer.dir ${hadoop.tmp.dir}/s3
fs.s3n.block.size 67108864
nfs.exports.allowed.hosts * rw
ha.health-monitor.connect-retry-interval.ms 1000
hadoop.security.instrumentation.requires.admin false
hadoop.registry.zk.retry.ceiling.ms 60000
nfs.rtmax 1048576
dfs.client.mmap.cache.size 256
dfs.datanode.data.dir.perm 700
io.file.buffer.size 4096
dfs.namenode.backup.address 0.0.0.0:50100
dfs.client.datanode-restart.timeout 30
dfs.datanode.readahead.bytes 4194304
dfs.namenode.xattrs.enabled true
io.mapfile.bloom.size 1048576
ipc.client.connect.retry.interval 1000
dfs.client-write-packet-size 65536
dfs.namenode.checkpoint.txns 1000000
dfs.datanode.bp-ready.timeout 20
dfs.datanode.transfer.socket.send.buffer.size 131072
hadoop.security.kms.client.authentication.retry-count 1
dfs.client.block.write.retries 3
fs.swift.impl org.apache.hadoop.fs.swift.snative.SwiftNativeFileSystem
ha.failover-controller.graceful-fence.connection.retries 1
hadoop.registry.zk.connection.timeout.ms 15000
dfs.namenode.safemode.threshold-pct 0.999f
dfs.cachereport.intervalMsec 10000
hadoop.security.java.secure.random.algorithm SHA1PRNG
ftp.blocksize 67108864
dfs.namenode.list.cache.directives.num.responses 100
dfs.namenode.kerberos.principal.pattern *
file.stream-buffer-size 4096
dfs.datanode.dns.nameserver default
fs.s3a.max.total.tasks 1000
dfs.namenode.replication.considerLoad true
nfs.allow.insecure.ports true
dfs.namenode.edits.journal-plugin.qjournal org.apache.hadoop.hdfs.qjournal.client.QuorumJournalManager
dfs.client.write.exclude.nodes.cache.expiry.interval.millis 600000
dfs.client.mmap.cache.timeout.ms 3600000
ipc.client.idlethreshold 4000
io.skip.checksum.errors false
ftp.stream-buffer-size 4096
fs.s3a.fast.upload false
dfs.client.failover.connection.retries.on.timeouts 0
file.blocksize 67108864
ftp.replication 3
dfs.namenode.replication.work.multiplier.per.iteration 2
hadoop.security.authorization false
hadoop.http.authentication.simple.anonymous.allowed true
s3native.client-write-packet-size 65536
hadoop.rpc.socket.factory.class.default org.apache.hadoop.net.StandardSocketFactory
file.bytes-per-checksum 512
dfs.datanode.slow.io.warning.threshold.ms 300
fs.har.impl.disable.cache true
rpc.engine.org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolPB org.apache.hadoop.ipc.ProtobufRpcEngine
io.seqfile.lazydecompress true
dfs.namenode.reject-unresolved-dn-topology-mapping false
hadoop.common.configuration.version 0.23.0
hadoop.security.authentication simple
dfs.datanode.drop.cache.behind.reads false
dfs.image.compression.codec org.apache.hadoop.io.compress.DefaultCodec
dfs.client.read.shortcircuit.streams.cache.size 256
file.replication 1
dfs.namenode.top.num.users 10
dfs.namenode.accesstime.precision 3600000
dfs.namenode.fs-limits.max-xattrs-per-inode 32
dfs.image.transfer.timeout 60000
io.mapfile.bloom.error.rate 0.005
nfs.wtmax 1048576
hadoop.security.kms.client.encrypted.key.cache.size 500
dfs.namenode.edit.log.autoroll.check.interval.ms 300000
fs.s3a.multipart.purge false
dfs.namenode.support.allow.format true
hadoop.hdfs.configuration.version 1
fs.s3a.connection.establish.timeout 5000
hadoop.security.group.mapping.ldap.search.attr.member member
dfs.secondary.namenode.kerberos.internal.spnego.principal ${dfs.web.authentication.kerberos.principal}
dfs.stream-buffer-size 4096
hadoop.ssl.client.conf ssl-client.xml
dfs.namenode.invalidate.work.pct.per.iteration 0.32f
fs.s3a.multipart.purge.age 86400
dfs.journalnode.https-address 0.0.0.0:8481
dfs.namenode.top.enabled true
hadoop.security.kms.client.encrypted.key.cache.low-watermark 0.3f
dfs.namenode.max.objects 0
hadoop.user.group.static.mapping.overrides dr.who=;
fs.s3a.fast.buffer.size 1048576
dfs.bytes-per-checksum 512
dfs.datanode.max.transfer.threads 4096
dfs.block.access.key.update.interval 600
ipc.maximum.data.length 67108864
tfile.fs.input.buffer.size 262144
ha.failover-controller.new-active.rpc-timeout.ms 60000
dfs.client.cached.conn.retry 3
dfs.client.read.shortcircuit false
hadoop.ssl.hostname.verifier DEFAULT
dfs.datanode.hdfs-blocks-metadata.enabled false
dfs.datanode.directoryscan.throttle.limit.ms.per.sec 0
dfs.image.transfer.chunksize 65536
hadoop.http.authentication.type simple
dfs.namenode.list.encryption.zones.num.responses 100
dfs.client.https.keystore.resource ssl-client.xml
s3native.blocksize 67108864
net.topology.impl org.apache.hadoop.net.NetworkTopology
dfs.client.failover.sleep.base.millis 500
io.seqfile.compress.blocksize 1000000
dfs.namenode.path.based.cache.refresh.interval.ms 30000
dfs.namenode.decommission.interval 30
dfs.permissions.superusergroup supergroup
dfs.namenode.fs-limits.max-directory-items 1048576
hadoop.registry.zk.retry.times 5
dfs.ha.log-roll.period 120
fs.AbstractFileSystem.ftp.impl org.apache.hadoop.fs.ftp.FtpFs
ftp.bytes-per-checksum 512
dfs.user.home.dir.prefix /user
dfs.namenode.checkpoint.edits.dir ${dfs.namenode.checkpoint.dir}
dfs.client.socket.send.buffer.size 131072
ipc.client.fallback-to-simple-auth-allowed false
dfs.blockreport.initialDelay 0
dfs.namenode.inotify.max.events.per.rpc 1000
dfs.namenode.heartbeat.recheck-interval 300000
dfs.namenode.safemode.extension 30000
dfs.client.failover.sleep.max.millis 15000
dfs.namenode.delegation.key.update-interval 86400000
dfs.datanode.transfer.socket.recv.buffer.size 131072
hadoop.rpc.protection authentication
fs.permissions.umask-mode 022
fs.s3.sleepTimeSeconds 10
dfs.namenode.fs-limits.max-xattr-size 16384
ha.health-monitor.rpc-timeout.ms 45000
hadoop.http.staticuser.user dr.who
dfs.datanode.http.address 0.0.0.0:50075
fs.s3a.connection.maximum 15
fs.s3a.paging.maximum 5000
fs.AbstractFileSystem.viewfs.impl org.apache.hadoop.fs.viewfs.ViewFs
dfs.namenode.blocks.per.postponedblocks.rescan 10000
fs.ftp.host 0.0.0.0
dfs.lock.suppress.warning.interval 10s
hadoop.http.authentication.kerberos.keytab ${user.home}/hadoop.keytab
fs.s3a.impl org.apache.hadoop.fs.s3a.S3AFileSystem
hadoop.registry.zk.root /registry
hadoop.jetty.logs.serve.aliases true
dfs.namenode.fs-limits.max-blocks-per-file 1048576
dfs.balancer.keytab.enabled false
dfs.client.block.write.replace-datanode-on-failure.enable true
hadoop.http.cross-origin.max-age 1800
io.compression.codec.bzip2.library system-native
dfs.namenode.checkpoint.dir file://${hadoop.tmp.dir}/dfs/namesecondary
dfs.client.use.legacy.blockreader.local false
dfs.namenode.top.windows.minutes 1,5,25
ipc.ping.interval 60000
net.topology.node.switch.mapping.impl org.apache.hadoop.net.ScriptBasedMapping
nfs.mountd.port 4242
dfs.storage.policy.enabled true
dfs.namenode.list.cache.pools.num.responses 100
fs.df.interval 60000
nfs.server.port 2049
ha.zookeeper.parent-znode /hadoop-ha
hadoop.http.cross-origin.allowed-headers X-Requested-With,Content-Type,Accept,Origin
dfs.datanode.block-pinning.enabled false
dfs.namenode.num.checkpoints.retained 2
fs.s3a.attempts.maximum 10
s3native.stream-buffer-size 4096
io.seqfile.local.dir ${hadoop.tmp.dir}/io/local
fs.s3n.multipart.copy.block.size 5368709120
dfs.encrypt.data.transfer.cipher.key.bitlength 128
dfs.client.mmap.retry.timeout.ms 300000
dfs.datanode.sync.behind.writes false
dfs.namenode.fslock.fair true
hadoop.ssl.keystores.factory.class org.apache.hadoop.security.ssl.FileBasedKeyStoresFactory
dfs.permissions.enabled true
fs.AbstractFileSystem.hdfs.impl org.apache.hadoop.fs.Hdfs
dfs.blockreport.split.threshold 1000000
dfs.datanode.balance.bandwidthPerSec 1048576
dfs.block.scanner.volume.bytes.per.second 1048576
hadoop.security.random.device.file.path /dev/urandom
fs.s3.maxRetries 4
hadoop.http.filter.initializers org.apache.hadoop.http.lib.StaticUserWebFilter
dfs.namenode.stale.datanode.interval 30000
ipc.client.rpc-timeout.ms 0
fs.client.resolve.remote.symlinks true
dfs.default.chunk.view.size 32768
hadoop.ssl.enabled.protocols TLSv1
dfs.namenode.decommission.blocks.per.interval 500000
dfs.namenode.handler.count 10
dfs.image.transfer.bandwidthPerSec 0
rpc.metrics.quantile.enable false
hadoop.ssl.enabled false
dfs.replication.max 512
dfs.namenode.name.dir /home/hadoop/data/hadoopdata/name
dfs.namenode.read-lock-reporting-threshold-ms 5000
dfs.datanode.https.address 0.0.0.0:50475
dfs.datanode.failed.volumes.tolerated 0
ipc.client.kill.max 10
fs.s3a.threads.max 256
ipc.server.listen.queue.size 128
dfs.client.domain.socket.data.traffic false
dfs.block.access.token.enable false
dfs.blocksize 134217728
fs.s3a.connection.timeout 50000
fs.s3a.threads.keepalivetime 60
file.client-write-packet-size 65536
dfs.datanode.address 0.0.0.0:50010
ha.failover-controller.cli-check.rpc-timeout.ms 20000
ha.zookeeper.acl world:anyone:rwcda
ipc.client.connect.max.retries 10
dfs.encrypt.data.transfer false
dfs.namenode.write.stale.datanode.ratio 0.5f
ipc.client.ping true
dfs.datanode.shared.file.descriptor.paths /dev/shm,/tmp
dfs.short.circuit.shared.memory.watcher.interrupt.check.ms 60000
hadoop.tmp.dir /home/hadoop/data/hadoopdata
dfs.datanode.handler.count 10
dfs.client.failover.max.attempts 15
dfs.balancer.max-no-move-interval 60000
dfs.client.read.shortcircuit.streams.cache.expiry.ms 300000
dfs.namenode.block-placement-policy.default.prefer-local-node true
hadoop.ssl.require.client.cert false
hadoop.security.uid.cache.secs 14400
dfs.client.read.shortcircuit.skip.checksum false
dfs.namenode.resource.checked.volumes.minimum 1
hadoop.registry.rm.enabled false
dfs.namenode.quota.init-threads 4
dfs.namenode.max.extra.edits.segments.retained 10000
dfs.webhdfs.user.provider.user.pattern ^[A-Za-z_][A-Za-z0-9._-]*[$]?$
dfs.client.mmap.enabled true
dfs.client.file-block-storage-locations.timeout.millis 1000
dfs.datanode.block.id.layout.upgrade.threads 12
dfs.datanode.use.datanode.hostname false
hadoop.fuse.timer.period 5
dfs.client.context default
fs.trash.checkpoint.interval 0
dfs.journalnode.http-address 0.0.0.0:8480
dfs.balancer.address 0.0.0.0:0
dfs.namenode.lock.detailed-metrics.enabled false
dfs.namenode.delegation.token.renew-interval 86400000
ha.health-monitor.check-interval.ms 1000
dfs.namenode.retrycache.heap.percent 0.03f
ipc.client.connect.timeout 20000
dfs.reformat.disabled false
dfs.blockreport.intervalMsec 21600000
fs.s3a.multipart.threshold 2147483647
dfs.https.server.keystore.resource ssl-server.xml
hadoop.http.cross-origin.enabled false
io.map.index.skip 0
dfs.balancer.block-move.timeout 0
io.native.lib.available true
s3.replication 3
dfs.namenode.kerberos.internal.spnego.principal ${dfs.web.authentication.kerberos.principal}
fs.AbstractFileSystem.har.impl org.apache.hadoop.fs.HarFs
hadoop.security.kms.client.encrypted.key.cache.num.refill.threads 2
fs.s3n.multipart.uploads.block.size 67108864
dfs.image.compress false
dfs.datanode.dns.interface default
dfs.datanode.available-space-volume-choosing-policy.balanced-space-preference-fraction 0.75f
tfile.fs.output.buffer.size 262144
fs.du.interval 600000
dfs.client.failover.connection.retries 0
dfs.namenode.edit.log.autoroll.multiplier.threshold 2.0
hadoop.security.group.mapping.ldap.ssl false
dfs.namenode.top.window.num.buckets 10
fs.s3a.buffer.dir ${hadoop.tmp.dir}/s3a
dfs.namenode.checkpoint.check.period 60
fs.defaultFS hdfs://hadoop1:9000
fs.s3a.multipart.size 104857600
dfs.client.slow.io.warning.threshold.ms 30000
dfs.datanode.max.locked.memory 0
dfs.namenode.retrycache.expirytime.millis 600000
hadoop.security.group.mapping.ldap.search.attr.group.name cn
dfs.client.block.write.replace-datanode-on-failure.best-effort false
dfs.ha.fencing.ssh.connect-timeout 30000
dfs.datanode.scan.period.hours 504
hadoop.registry.zk.quorum localhost:2181
dfs.namenode.fs-limits.max-component-length 255
hadoop.http.cross-origin.allowed-origins *
dfs.namenode.enable.retrycache true
dfs.datanode.du.reserved 0
dfs.datanode.ipc.address 0.0.0.0:50020
hadoop.registry.system.acls sasl:yarn@, sasl:mapred@, sasl:hdfs@
dfs.namenode.path.based.cache.retry.interval.ms 30000
hadoop.security.crypto.cipher.suite AES/CTR/NoPadding
dfs.client.block.write.replace-datanode-on-failure.policy DEFAULT
dfs.namenode.http-address 0.0.0.0:50070
hadoop.security.crypto.codec.classes.aes.ctr.nopadding org.apache.hadoop.crypto.OpensslAesCtrCryptoCodec,org.apache.hadoop.crypto.JceAesCtrCryptoCodec
dfs.ha.tail-edits.period 60
hadoop.security.groups.negative-cache.secs 30
hadoop.ssl.server.conf ssl-server.xml
hadoop.registry.jaas.context Client
s3native.replication 3
hadoop.security.group.mapping.ldap.search.filter.group (objectClass=group)
hadoop.http.authentication.kerberos.principal HTTP/_HOST@LOCALHOST
dfs.namenode.startup.delay.block.deletion.sec 0
hadoop.security.group.mapping.ldap.search.filter.user (&(objectClass=user)(sAMAccountName={0}))
dfs.namenode.edits.dir ${dfs.namenode.name.dir}
dfs.namenode.checkpoint.max-retries 3
s3.stream-buffer-size 4096
ftp.client-write-packet-size 65536
dfs.datanode.fsdatasetcache.max.threads.per.volume 4
hadoop.security.sensitive-config-keys password$,fs.s3.*[Ss]ecret.?[Kk]ey,fs.azure.account.key.*,dfs.webhdfs.oauth2.[a-z]+.token,hadoop.security.sensitive-config-keys
dfs.namenode.decommission.max.concurrent.tracked.nodes 100
dfs.namenode.name.dir.restore false
ipc.server.log.slow.rpc false
dfs.heartbeat.interval 3
dfs.namenode.secondary.http-address hadoop3:50090
ha.zookeeper.session-timeout.ms 5000
s3.bytes-per-checksum 512
fs.s3a.connection.ssl.enabled true
hadoop.http.authentication.signature.secret.file ${user.home}/hadoop-http-auth-signature-secret
hadoop.fuse.connection.timeout 300
dfs.namenode.checkpoint.period 3600
ipc.server.max.connections 0
dfs.ha.automatic-failover.enabled false
3、列出指定目录下的文件以及块的信息
package com.exam.hdfs; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.BlockLocation;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocatedFileStatus;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.fs.RemoteIterator; public class TestHDFS1 { public static void main(String[] args) throws Exception { Configuration conf = new Configuration();
System.setProperty("HADOOP_USER_NAME", "hadoop");
conf.set("fs.defaultFS", "hdfs://hadoop1:9000");
FileSystem fs = FileSystem.get(conf); /**
* 列出指定的目录下的所有文件
*/
RemoteIterator<LocatedFileStatus> listFiles = fs.listFiles(new Path("/"), true);
while(listFiles.hasNext()){
LocatedFileStatus file = listFiles.next(); System.out.println(file.getPath()+"\t");
System.out.println(file.getPath().getName()+"\t");
System.out.println(file.getLen()+"\t");
System.out.println(file.getReplication()+"\t"); /**
* blockLocations的长度是几？ 是什么意义？
*
* 块的数量
*/
BlockLocation[] blockLocations = file.getBlockLocations();
System.out.println(blockLocations.length+"\t"); for(BlockLocation bl : blockLocations){
String[] hosts = bl.getHosts(); System.out.print(hosts[0] + "-" + hosts[1]+"\t");
}
System.out.println(); } }
}
输出结果
hdfs://hadoop1:9000/aa/bb/cc/hadoop.tar.gz
hadoop.tar.gz
199007110
2
3
hadoop3-hadoop1 hadoop1-hadoop2 hadoop1-hadoop4
4、上传文件
package com.exam.hdfs; import java.io.File;
import java.io.FileInputStream;
import java.io.InputStream; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataOutputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IOUtils; public class UploadDataByStream { public static void main(String[] args) throws Exception { Configuration conf = new Configuration();
System.setProperty("HADOOP_USER_NAME", "hadoop");
conf.set("fs.defaultFS", "hdfs://hadoop1:9000");
FileSystem fs = FileSystem.get(conf); InputStream in = new FileInputStream(new File("d:/abc.tar.gz"));
FSDataOutputStream out = fs.create(new Path("/aa/abc.tar.gz")); IOUtils.copyBytes(in, out, 4096, true); fs.close(); }
}
5、下载文件
package com.exam.hdfs; import java.io.File;
import java.io.FileOutputStream;
import java.io.OutputStream; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IOUtils; public class DownloadDataByStream { public static void main(String[] args) throws Exception { Configuration conf = new Configuration();
System.setProperty("HADOOP_USER_NAME", "hadoop");
conf.set("fs.defaultFS", "hdfs://hadoop1:9000");
FileSystem fs = FileSystem.get(conf); FSDataInputStream in = fs.open(new Path("/aa/abc.tar.gz"));
OutputStream out = new FileOutputStream(new File("D:/abc.sh")); IOUtils.copyBytes(in, out, 4096, true); fs.close(); }
}
6、删除某个路径下特定类型的文件，比如class类型文件，比如txt类型文件
package com.exam.hdfs; import java.net.URI; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path; public class HDFS_DELETE_CLASS { public static final String FILETYPE = "tar.gz";
public static final String DELETE_PATH = "/aa"; public static void main(String[] args) throws Exception { new HDFS_DELETE_CLASS().rmrClassFile(new Path(DELETE_PATH));
} public void rmrClassFile(Path path) throws Exception{ // 首先获取集群必要的信息，以得到FileSystem的示例对象fs
Configuration conf = new Configuration();
FileSystem fs = FileSystem.get(new URI("hdfs://hadoop1:9000"), conf, "hadoop"); // 首先检查path本身是文件夹还是目录
FileStatus fileStatus = fs.getFileStatus(path);
boolean directory = fileStatus.isDirectory(); // 根据该目录是否是文件或者文件夹进行相应的操作
if(directory){
// 如果是目录
checkAndDeleteDirectory(path, fs);
}else{
// 如果是文件，检查该文件名是不是FILETYPE类型的文件
checkAndDeleteFile(path, fs);
}
} // 处理目录
public static void checkAndDeleteDirectory(Path path, FileSystem fs) throws Exception{
// 查看该path目录下一级子目录和子文件的状态
FileStatus[] listStatus = fs.listStatus(path);
for(FileStatus fStatus: listStatus){
Path p = fStatus.getPath();
// 如果是文件，并且是以FILETYPE结尾，则删掉，否则继续遍历下一级目录
if(fStatus.isFile()){
checkAndDeleteFile(p, fs);
}else{
checkAndDeleteDirectory(p, fs);
}
}
} // 檢查文件是否符合刪除要求，如果符合要求則刪除，不符合要求则不做处理
public static void checkAndDeleteFile(Path path, FileSystem fs) throws Exception{
String name = path.getName();
System.out.println(name);
/*// 直接判断有没有FILETYPE这个字符串,不是特别稳妥，并且会有误操作，所以得判断是不是以FILETYPE结尾
if(name.indexOf(FILETYPE) != -1){
fs.delete(path, true);
}*/
// 判断是不是以FILETYPE结尾
int startIndex = name.length() - FILETYPE.length();
int endIndex = name.length();
// 求得文件后缀名
String fileSuffix = name.substring(startIndex, endIndex);
if(fileSuffix.equals(FILETYPE)){
fs.delete(path, true);
}
}
}
7、删除HDFS集群中的所有空文件和空目录
public class DeleteEmptyDirAndFile {
static FileSystem fs = null;
public static void main(String[] args) throws Exception {
initFileSystem();
// 创建测试数据
// makeTestData();
// 删除测试数据
// deleteTestData();
// 删除指定文件夹下的空文件和空文件夹
deleteEmptyDirAndFile(new Path("/aa"));
}
/**
* 删除指定文件夹下的 空文件 和 空文件夹
* @throws Exception
*/
public static void deleteEmptyDirAndFile(Path path) throws Exception {
//当是空文件夹时
FileStatus[] listStatus = fs.listStatus(path);
if(listStatus.length == 0){
fs.delete(path, true);
return;
}
// 该方法的结果：包括指定目录的 文件 和 文件夹
RemoteIterator<LocatedFileStatus> listLocatedStatus = fs.listLocatedStatus(path);
while (listLocatedStatus.hasNext()) {
LocatedFileStatus next = listLocatedStatus.next();
Path currentPath = next.getPath();
// 获取父目录
Path parent = next.getPath().getParent();
// 如果是文件夹，继续往下遍历，删除符合条件的文件（空文件夹）
if (next.isDirectory()) {
// 如果是空文件夹
if(fs.listStatus(currentPath).length == 0){
// 删除掉
fs.delete(currentPath, true);
}else{
// 不是空文件夹，那么则继续遍历
if(fs.exists(currentPath)){
deleteEmptyDirAndFile(currentPath);
}
}
// 如果是文件
} else {
// 获取文件的长度
long fileLength = next.getLen();
// 当文件是空文件时， 删除
if(fileLength == 0){
fs.delete(currentPath, true);
}
}
// 当空文件夹或者空文件删除时，有可能导致父文件夹为空文件夹，
// 所以每次删除一个空文件或者空文件的时候都需要判断一下，如果真是如此，那么就需要把该文件夹也删除掉
int length = fs.listStatus(parent).length;
if(length == 0){
fs.delete(parent, true);
}
}
}
/**
* 初始化FileSystem对象之用
*/
public static void initFileSystem() throws Exception{
Configuration conf = new Configuration();
System.setProperty("HADOOP_USER_NAME", "hadoop");
conf.addResource("config/core-site.xml");
conf.addResource("config/hdfs-site.xml");
fs = FileSystem.get(conf);
}
/**
* 创建 测试 数据之用
*/
public static void makeTestData() throws Exception {
String emptyFilePath = "D:\\bigdata\\1704mr_test\\empty.txt";
String notEmptyFilePath = "D:\\bigdata\\1704mr_test\\notEmpty.txt";
// 空文件夹 和 空文件 的目录
String path1 = "/aa/bb1/cc1/dd1/";
fs.mkdirs(new Path(path1));
fs.mkdirs(new Path("/aa/bb1/cc1/dd2/"));
fs.copyFromLocalFile(new Path(emptyFilePath), new Path(path1));
fs.copyFromLocalFile(new Path(notEmptyFilePath), new Path(path1));
// 空文件 的目录
String path2 = "/aa/bb1/cc2/dd2/";
fs.mkdirs(new Path(path2));
fs.copyFromLocalFile(new Path(emptyFilePath), new Path(path2));
// 非空文件 的目录
String path3 = "/aa/bb2/cc3/dd3";
fs.mkdirs(new Path(path3));
fs.copyFromLocalFile(new Path(notEmptyFilePath), new Path(path3));
// 空 文件夹
String path4 = "/aa/bb2/cc4/dd4";
fs.mkdirs(new Path(path4));
System.out.println("测试数据创建成功");
}
/**
* 删除 指定文件夹
* @throws Exception
*/
public static void deleteTestData() throws Exception {
boolean delete = fs.delete(new Path("/aa"), true);
System.out.println(delete ? "删除数据成功" : "删除数据失败");
}
}
8、手动拷贝某个特定的数据块（比如某个文件的第二个数据块）
/**
* 手动拷贝某个特定的数据块（比如某个文件的第二个数据块）
* */
public static void copyBlock(String str,int num) { Path path = new Path(str); BlockLocation[] localtions = new BlockLocation[0] ; try {
FileStatus fileStatus = fs.getFileStatus(path); localtions = fs.getFileBlockLocations(fileStatus, 0, fileStatus.getLen()); /*for(int i=0;i<localtions.length;i++) {
//0,134217728,hadoop1,hadoop3
//134217728,64789382,hadoop3,hadoop1
System.out.println(localtions[i]);
}*/ /*System.out.println(localtions[num-1].getOffset());
System.out.println(localtions[num-1].getLength());
String[] hosts = localtions[num-1].getHosts();*/ FSDataInputStream open = fs.open(path);
open.seek(localtions[num-1].getOffset());
OutputStream out = new FileOutputStream(new File("D:/abc.tar.gz"));
IOUtils.copyBytes(open, out,4096,true); } catch (IOException e) {
e.printStackTrace();
} }
9、编写程序统计出HDFS文件系统中文件大小小于HDFS集群中的默认块大小的文件占比
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocatedFileStatus;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.fs.RemoteIterator; /**
*
* 编写程序统计出HDFS文件系统中文件大小小于HDFS集群中的默认块大小的文件占比
* 比如：大于等于128M的文件个数为98，小于128M的文件总数为2，所以答案是2%
*/
public class Exam1_SmallFilePercent { private static int DEFAULT_BLOCKSIZE = 128 * 1024 * 1024; public static void main(String[] args) throws Exception { Configuration conf = new Configuration();
conf.set("fs.defaultFS", "hdfs://hadoop1:9000");
System.setProperty("HADOOP_USER_NAME", "hadoop");
FileSystem fs = FileSystem.get(conf); Path path = new Path("/");
float smallFilePercent = getSmallFilePercent(fs, path);
System.out.println(smallFilePercent); fs.close();
} /**
* 该方法求出指定目录下的小文件和总文件数的对比
* @throws Exception
*/
private static float getSmallFilePercent(FileSystem fs, Path path) throws Exception {
// TODO Auto-generated method stub int smallFile = 0;
int totalFile = 0; RemoteIterator<LocatedFileStatus> listFiles = fs.listFiles(path, false);
while(listFiles.hasNext()){
totalFile++;
LocatedFileStatus next = listFiles.next();
long len = next.getLen();
if(len < DEFAULT_BLOCKSIZE){
smallFile++;
}
}
System.out.println(smallFile+" : "+totalFile); return smallFile * 1f /totalFile;
} }
10、编写程序统计出HDFS文件系统中的平均数据块数（数据块总数/文件总数）
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocatedFileStatus;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.fs.RemoteIterator; /**
*
* 编写程序统计出HDFS文件系统中的平均数据块数（数据块总数/文件总数）
* 比如：一个文件有5个块，一个文件有3个块，那么平均数据块数为4
* 如果还有一个文件，并且数据块就1个，那么整个HDFS的平均数据块数就是3
*/
public class Exam2_HDSFAvgBlocks { public static void main(String[] args) throws Exception { Configuration conf = new Configuration();
conf.set("fs.defaultFS", "hdfs://hadoop1:9000");
System.setProperty("HADOOP_USER_NAME", "hadoop");
FileSystem fs = FileSystem.get(conf); Path path = new Path("/");
float avgHDFSBlocks = getHDFSAvgBlocks(fs, path);
System.out.println("HDFS的平均数据块个数为：" + avgHDFSBlocks); fs.close();
} /**
* 求出指定目录下的所有文件的平均数据块个数
*/
private static float getHDFSAvgBlocks(FileSystem fs, Path path) throws Exception {
// TODO Auto-generated method stub int totalFiles = 0; // 总文件数
int totalBlocks = 0; // 总数据块数 RemoteIterator<LocatedFileStatus> listFiles = fs.listFiles(path, false); while(listFiles.hasNext()){
LocatedFileStatus next = listFiles.next();
int length = next.getBlockLocations().length;
totalBlocks += length;
if(next.getLen() != 0){
totalFiles++;
}
}
System.out.println(totalBlocks+" : "+totalFiles); return totalBlocks * 1f / totalFiles;
} }
11、编写程序统计出HDFS文件系统中的平均副本数（副本总数/总数据块数）
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocatedFileStatus;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.fs.RemoteIterator; /**
* 编写程序统计出HDFS文件系统中的平均副本数（副本总数/总数据块数）
* 比如：总共两个文件，一个文件5个数据块，每个数据块3个副本，第二个文件2个数据块，每个文件2个副本，最终的平均副本数 = （3*3 + 2*2）/（3+2）= 2.8
*/
public class Exam3_HDSFAvgBlockCopys { public static void main(String[] args) throws Exception { Configuration conf = new Configuration();
conf.set("fs.defaultFS", "hdfs://hadoop02:9000");
System.setProperty("HADOOP_USER_NAME", "hadoop");
FileSystem fs = FileSystem.get(conf); Path path = new Path("/");
float avgHDFSBlockCopys = getHDFSAvgBlockCopys(fs, path);
System.out.println("HDFS的平均数据块个数为：" + avgHDFSBlockCopys); fs.close();
} /**
* 求出指定目录下的所有文件的平均数据块个数
*/
private static float getHDFSAvgBlockCopys(FileSystem fs, Path path) throws Exception {
// TODO Auto-generated method stub int totalCopy = 0; // 总副本数
int totalBlocks = 0; // 总数据块数 RemoteIterator<LocatedFileStatus> listFiles = fs.listFiles(path, false); while(listFiles.hasNext()){
LocatedFileStatus next = listFiles.next(); int length = next.getBlockLocations().length;
short replication = next.getReplication(); totalBlocks += length;
totalCopy += length * replication;
}
System.out.println(totalCopy+" : "+totalBlocks); return totalCopy * 1f / totalBlocks;
} }
12、统计HDFS整个文件系统中的不足指定数据块大小的数据块的比例
import java.io.IOException; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.BlockLocation;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.LocatedFileStatus;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.fs.RemoteIterator; /**
* 统计HDFS整个文件系统中的不足指定数据块大小的数据块的比例
* 比如指定的数据块大小是128M，总数据块有100个，不是大小为完整的128M的数据块有5个，那么不足指定数据块大小的数据块的比例就为5%
* 注意：千万注意考虑不同文件的指定数据块大小可能不一致。所以千万不能用默认的128M一概而论
*/
public class Exam4_LTBlockSize { public static void main(String[] args) throws Exception { Configuration conf = new Configuration();
conf.set("fs.defaultFS", "hdfs://hadoop02:9000");
System.setProperty("HADOOP_USER_NAME", "hadoop");
FileSystem fs = FileSystem.get(conf); Path path = new Path("/");
float avgHDFSBlockCopys = getLessThanBlocksizeBlocks(fs, path);
System.out.println("HDFS的不足指定数据块大小的数据块数目为：" + avgHDFSBlockCopys); fs.close();
} private static float getLessThanBlocksizeBlocks(FileSystem fs, Path path) throws Exception {
// TODO Auto-generated method stub int totalBlocks = 0; // 总副本数
int lessThenBlocksizeBlocks = 0; // 总数据块数 RemoteIterator<LocatedFileStatus> listFiles = fs.listFiles(path, false); while(listFiles.hasNext()){
LocatedFileStatus next = listFiles.next(); BlockLocation[] blockLocations = next.getBlockLocations();
int length = blockLocations.length; if(length != 0){
totalBlocks += length;
long lastBlockSize = blockLocations[length - 1].getLength();
long blockSize = next.getBlockSize();
if(lastBlockSize < blockSize){
lessThenBlocksizeBlocks++;
}
}
}
System.out.println(lessThenBlocksizeBlocks+" : "+totalBlocks); return lessThenBlocksizeBlocks * 1f / totalBlocks;
}
}
13、统计出一个给定数组的蓄水总量（把数组的每个位置的数看是做地势高低）
/**
统计出一个给定数组的蓄水总量（把数组的每个位置的数看是做地势高低）
比如：int[] intArray = new int[]{4,3,2,5,6,4,4,7}
能蓄水：[0,1,2,0,0,2,2,0] 所以总量是：7 核心思路：把数组切成很多个 01数组，每一层一个01数组，统计每个01数组中的合法0的总个数（数组的左边第一个1的中间区间中的0的个数）即可
*/
public class Exam5_WaterStoreOfArray { public static void main(String[] args) { // int[] intArray = new int[]{4,3,2,5,6,4,4,7};
// int[] intArray = new int[]{1,2,3,4,5,6};
int[] intArray = new int[]{3,1,2,7,3,8,4,9,5,6}; int totalWater = getArrayWater(intArray);
System.out.println(totalWater);
} /**
* 求出数组中的水数
*/
private static int getArrayWater(int[] intArray) { int findMaxValueOfArray = findMaxValueOfArray(intArray);
int findMinValueOfArray = findMinValueOfArray(intArray);
int length = intArray.length; int totalWater = 0; // 循环次数就是最大值和最小值的差
for(int i=findMinValueOfArray; i<findMaxValueOfArray; i++){
// 循环构造每一层的01数组
int[] tempArray = new int[length];
for(int j=0; j<length; j++){
if(intArray[j] > i){
tempArray[j] = 1;
}else{
tempArray[j] = 0;
}
}
// 获取每一个01数组的合法0个数
int waterOfOneZeroArray = getWaterOfOneZeroArray(tempArray);
totalWater += waterOfOneZeroArray;
}
return totalWater;
} /**
* 寻找逻辑是：从左右开始各找一个1，然后这两个1之间的所有0的个数，就是水数
*/
private static int getWaterOfOneZeroArray(int[] tempArray) { int length = tempArray.length;
int toatalWater = 0; // 找左边的1
int i = 0;
while(i < length){
if(tempArray[i] == 1){
break;
}
i++;
} // 从右边开始找1
int j=length-1;
while(j >= i){
if(tempArray[j] == 1){
break;
}
j--;
} // 找以上两个1之间的0的个数。
if(i == j || i + 1 == j){
return 0;
}else{
for(int k=i+1; k<j; k++){
if(tempArray[k] == 0){
toatalWater++;
}
}
return toatalWater;
}
} /**
*
* 描述：找出一个数组中的最大值
*/
public static int findMaxValueOfArray(int[] intArray){
int length = intArray.length;
if(length == 0){
return 0;
}else if(length == 1){
return intArray[0];
}else{
int max = intArray[0];
for(int i=1; i<length; i++){
if(intArray[i] > max){
max = intArray[i];
}
}
return max;
}
} /**
* 找出一个数组中的最小值
*/
public static int findMinValueOfArray(int[] intArray){
int length = intArray.length;
if(length == 0){
return 0;
}else if(length == 1){
return intArray[0];
}else{
int min = intArray[0];
for(int i=1; i<length; i++){
if(intArray[i] < min){
min = intArray[i];
}
}
return min;
}
}
}
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