1. 简介
2. 安装步骤及问题小记
3. 部署配置
4. Java客户端测试
5. 参考资料
1. 下面的安装部署基于Linux系统环境:centos 6(64位),其它Linux版本可能有所差异。
2. 网上有人说tair安装失败可能是因为gcc版本问题,高版本的gcc可能不支持某些特性导致安装失败,经过实验证明,该说法是错误的,tair安装失败有各种可能的原因但绝对与gcc版本无关,比如我的gcc开始版本为4.4.7,后来tair安装失败,我重新编译低版本的gcc(gcc4.1.2),但是问题同样出现。后来发现是其它原因,修正后重新用高版本gcc4.4.7安装成功。
3. 下面的内容部分参考tair官方介绍文档,转载请注明原文地址。
tair 是淘宝自己开发的一个分布式 key/value 存储引擎. tair 分为持久化和非持久化两种使用方式. 非持久化的 tair 可以看成是一个分布式缓存. 持久化的 tair 将数据存放于磁盘中. 为了解决磁盘损坏导致数据丢失, tair 可以配置数据的备份数目, tair 自动将一份数据的不同备份放到不同的主机上, 当有主机发生异常, 无法正常提供服务的时候, 其余的备份会继续提供服务.
2. 安装步骤及问题小记
2.1 安装步骤
由于tair的实现用到了底层库 tbsys 和 tbnet,因此在安装tair之前需要先安装依赖库 tbsys 和 tbnet。
2.1.1 获取源代码
首先需要通过svn下载源码,可以通过sudo yum install subversion安装svn服务。
- svn checkout http://code.taobao.org/svn/tb-common-utils/trunk/ tb-common-utils # 获取tbsys 和 tbnet的源代码
- svn checkout http://code.taobao.org/svn/tair/trunk/ tair # 获取tair源代码
2.1.2 安装依赖库或软件
编译tair或tbnet/tbsys之前需要预先安装一些编译所需的依赖库或软件。在安装这些依赖之前最好首先检查系统是否已经安装,在用rpm管理软件包的os上可以使用rpm -q 软件包名查看是否已安装该软件或库。
a. 安装libtoolsudo yum install libtool # 同时会安装libtool所依赖的automake和autoconfigb. 安装boost-devel库sudo yum install boost-develc. 安装zlib库sudo yum install zlib-devel2.1.3 编译安装tbsys和tbnet
- tair 的底层依赖于tbsys库和tbnet库, 所以要先编译安装这两个库.
- a. 设置环境变量 TBLIB_ROOT
取得源代码后, 先指定环境变量 TBLIB_ROOT 为需要安装的目录. 这个环境变量在后续 tair 的编译安装中仍旧会被使用到.比如要安装到当前用户的lib目录下, 则指定export TBLIB_ROOT="~/lib"。
b. 安装进入源码目录, 执行build.sh进行安装.
- 2.1.4 编译安装tair
进入 tair 源码目录,依次按以下顺序编译安装./bootstrap.sh ./configure # 注意, 在运行configue的时候, 可以使用 --with-boost=xxxx 来指定boost的目录. 使用--with-release=yes 来编译release版本. make make install
安装成功后会在当前用户home目录下生成文件夹tair_bin,即tair的安装成功后的目录。
2.2 问题小记
安装过程并不是一帆风顺的,期间出现了很多问题,在此简单记录以供参考。
2.2.1 g++未安装
说明安装了gcc但未安装g++,而tair是用C++开发的,因此只能用g++编译,通过过sudo yum install gcc-c++安装即可。checking for C++ compiler default output file name...configure: error: in `/home/config_server/tair/tb-common-utils/tbnet‘:configure: error: C++ compiler cannot create executablesSee `config.log‘ for more details.make: *** No targets specified and no makefile found. Stop.make: *** No rule to make target `install‘. Stop.
2.2.2 头文件路径错误
因为tbnet和tbsys在两个不同的目录,但它们的源码文件里头文件的互相引用却没有加绝对或相对路径,将两个目录的源码加入到C++环境变量中即可。In file included from channel.cpp:16: tbnet.h:39:19: error: tbsys.h: No such file or directory databuffer.h: In member function ‘void tbnet::DataBuffer::expand(int)‘: databuffer.h:429: error: ‘ERROR‘ was not declared in this scope databuffer.h:429: error: ‘TBSYS_LOG‘ was not declared in this scope socket.h: At global scope: socket.h:191: error: ‘tbsys‘ has not been declared socket.h:191: error: ISO C++ forbids declaration of ‘CThreadMutex‘ with no type socket.h:191: error: expected ‘;‘ before ‘_dnsMutex‘ channelpool.h:85: error: ‘tbsys‘ has not been declared channelpool.h:85: error: ISO C++ forbids declaration of ‘CThreadMutex‘ with no type channelpool.h:85: error: expected ‘;‘ before ‘_mutex‘ channelpool.h:93: error: ‘atomic_t‘ does not name a type channelpool.h:94: error: ‘atomic_t‘ does not name a type connection.h:164: error: ‘tbsys‘ has not been declared connection.h:164: error: ISO C++ forbids declaration of ‘CThreadCond‘ with no type connection.h:164: error: expected ‘;‘ before ‘_outputCond‘ iocomponent.h:184: error: ‘atomic_t‘ does not name a type iocomponent.h: In member function ‘int tbnet::IOComponent::addRef()‘: iocomponent.h:108: error: ‘_refcount‘ was not declared in this scope iocomponent.h:108: error: ‘atomic_add_return‘ was not declared in this scope iocomponent.h: In member function ‘void tbnet::IOComponent::subRef()‘: iocomponent.h:115: error: ‘_refcount‘ was not declared in this scope iocomponent.h:115: error: ‘atomic_dec‘ was not declared in this scope iocomponent.h: In member function ‘int tbnet::IOComponent::getRef()‘: iocomponent.h:122: error: ‘_refcount‘ was not declared in this scope iocomponent.h:122: error: ‘atomic_read‘ was not declared in this scope transport.h: At global scope: transport.h:23: error: ‘tbsys‘ has not been declared transport.h:23: error: expected `{‘ before ‘Runnable‘ transport.h:23: error: invalid function declaration packetqueuethread.h:28: error: ‘tbsys‘ has not been declared packetqueuethread.h:28: error: expected `{‘ before ‘CDefaultRunnable‘ packetqueuethread.h:28: error: invalid function declaration connectionmanager.h:93: error: ‘tbsys‘ has not been declared connectionmanager.h:93: error: ISO C++ forbids declaration of ‘CThreadMutex‘ with no type connectionmanager.h:93: error: expected ‘;‘ before ‘_mutex‘ make[1]: *** [channel.lo] Error 1 make[1]: Leaving directory `/home/tair/tair/tb-common-utils/tbnet/src‘ make: *** [install-recursive] Error 1have installed in ~/libCPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/home/tair/tair/tb-common-utils/tbsys/src:/home/tair/tair/tb-common-utils/tbnet/srcexport CPLUS_INCLUDE_PATH
3. 部署配置
tair的运行, 至少需要一个 config server 和一个 data server. 推荐使用两个 config server 多个data server的方式. 两个config server有主备之分.tair有三个配置文件,分别是对config server、data server及group信息的配置,在tair_bin安装目录下的etc目录下有这三个配置文件的样例,我们将其复制一下,成为我们需要的配置文件。cp configserver.conf.default configserver.conf cp dataserver.conf.default dataserver.conf cp group.conf.default group.conf
我的部署环境:
在配置之前,请查阅官网给出的配置文件字段详解,下面直接贴出我自己的配置并加以简单的说明。
3.1 配置config server
#
# tair 2.3 --- configserver config
#
[public]
config_server=10.10.7.144:51980
config_server=10.10.7.144:51980
[configserver]
port=51980
log_file=/home/dataserver1/tair_bin/logs/config.log
pid_file=/home/dataserver1/tair_bin/logs/config.pid
log_level=warn
group_file=/home/dataserver1/tair_bin/etc/group.conf
data_dir=/home/dataserver1/tair_bin/data/data
dev_name=venet0:0
注意事项:
(1)首先需要配置config server的服务器地址和端口号,端口号可以默认,服务器地址改成自己的,有一主一备两台configserver,这里仅为测试使用就设置为一台了。
(2)log_file/pid_file等的路径设置最好用绝对路径,默认的是相对路径,而且是不正确的相对路径(没有返回上级目录),因此这里需要修改。注意data文件和log文件非常重要,data文件不可缺少,而log文件是部署出错后能给你详细的出错原因。
(3)dev_name很重要,需要设置为你自己当前网络接口的名称,默认为eth0,这里我根据自己的网络情况进行了修改(ifconfig查看网络接口名称)。
#
# tair 2.3 --- tairserver config
#
[public]
config_server=10.10.7.144:51980
config_server=10.10.7.144:51980
[tairserver]
#
#storage_engine:
#
# mdb
# kdb
# ldb
#
storage_engine=ldb
local_mode=0
#
#mdb_type:
# mdb
# mdb_shm
#
mdb_type=mdb_shm
#
# if you just run 1 tairserver on a computer, you may ignore this option.
# if you want to run more than 1 tairserver on a computer, each tairserver must have their own "mdb_shm_path"
#
#
mdb_shm_path=/mdb_shm_path01
#tairserver listen port
port=51910
heartbeat_port=55910
process_thread_num=16
#
#mdb size in MB
#
slab_mem_size=1024
log_file=/home/dataserver1/tair_bin/logs/server.log
pid_file=/home/dataserver1/tair_bin/logs/server.pid
log_level=warn
dev_name=venet0:0
ulog_dir=/home/dataserver1/tair_bin/data/ulog
ulog_file_number=3
ulog_file_size=64
check_expired_hour_range=2-4
check_slab_hour_range=5-7
dup_sync=1
do_rsync=0
# much resemble json format
# one local cluster config and one or multi remote cluster config.
# {local:[master_cs_addr,slave_cs_addr,group_name,timeout_ms,queue_limit],remote:[...],remote:[...]}
rsync_conf={local:[10.0.0.1:5198,10.0.0.2:5198,group_local,2000,1000],remote:[10.0.1.1:5198,10.0.1.2:5198,group_remote,2000,3000]}
# if same data can be updated in local and remote cluster, then we need care modify time to
# reserve latest update when do rsync to each other.
rsync_mtime_care=0
# rsync data directory(retry_log/fail_log..)
rsync_data_dir=/home/dataserver1/tair_bin/data/remote
# max log file size to record failed rsync data, rotate to a new file when over the limit
rsync_fail_log_size=30000000
# whether do retry when rsync failed at first time
rsync_do_retry=0
# when doing retry, size limit of retry log‘s memory use
rsync_retry_log_mem_size=100000000
[fdb]
# in MB
index_mmap_size=30
cache_size=256
bucket_size=10223
free_block_pool_size=8
data_dir=/home/dataserver1/tair_bin/data/fdb
fdb_name=tair_fdb
[kdb]
# in byte
map_size=10485760 # the size of the internal memory-mapped region
bucket_size=1048583 # the number of buckets of the hash table
record_align=128 # the power of the alignment of record size
data_dir=/home/dataserver1/tair_bin/data/kdb # the directory of kdb‘s data
[ldb]
#### ldb manager config
## data dir prefix, db path will be data/ldbxx, "xx" means db instance index.
## so if ldb_db_instance_count = 2, then leveldb will init in
## /data/ldb1/ldb/, /data/ldb2/ldb/. We can mount each disk to
## data/ldb1, data/ldb2, so we can init each instance on each disk.
data_dir=/home/dataserver1/tair_bin/data/ldb
## leveldb instance count, buckets will be well-distributed to instances
ldb_db_instance_count=1
## whether load backup version when startup.
## backup version may be created to maintain some db data of specifid version.
ldb_load_backup_version=0
## whether support version strategy.
## if yes, put will do get operation to update existed items‘s meta info(version .etc),
## get unexist item is expensive for leveldb. set 0 to disable if nobody even care version stuff.
ldb_db_version_care=1
## time range to compact for gc, 1-1 means do no compaction at all
ldb_compact_gc_range = 3-6
## backgroud task check compact interval (s)
ldb_check_compact_interval = 120
## use cache count, 0 means NOT use cache,`ldb_use_cache_count should NOT be larger
## than `ldb_db_instance_count, and better to be a factor of `ldb_db_instance_count.
## each cache mdb‘s config depends on mdb‘s config item(mdb_type, slab_mem_size, etc)
ldb_use_cache_count=1
## cache stat can‘t report configserver, record stat locally, stat file size.
## file will be rotate when file size is over this.
ldb_cache_stat_file_size=20971520
## migrate item batch size one time (1M)
ldb_migrate_batch_size = 3145728
## migrate item batch count.
## real batch migrate items depends on the smaller size/count
ldb_migrate_batch_count = 5000
## comparator_type bitcmp by default
# ldb_comparator_type=numeric
## numeric comparator: special compare method for user_key sorting in order to reducing compact
## parameters for numeric compare. format: [meta][prefix][delimiter][number][suffix]
## skip meta size in compare
# ldb_userkey_skip_meta_size=2
## delimiter between prefix and number
# ldb_userkey_num_delimiter=:
####
## use blommfilter
ldb_use_bloomfilter=1
## use mmap to speed up random acess file(sstable),may cost much memory
ldb_use_mmap_random_access=0
## how many highest levels to limit compaction
ldb_limit_compact_level_count=0
## limit compaction ratio: allow doing one compaction every ldb_limit_compact_interval
## 0 means limit all compaction
ldb_limit_compact_count_interval=0
## limit compaction time interval
## 0 means limit all compaction
ldb_limit_compact_time_interval=0
## limit compaction time range, start == end means doing limit the whole day.
ldb_limit_compact_time_range=6-1
## limit delete obsolete files when finishing one compaction
ldb_limit_delete_obsolete_file_interval=5
## whether trigger compaction by seek
ldb_do_seek_compaction=0
## whether split mmt when compaction with user-define logic(bucket range, eg)
ldb_do_split_mmt_compaction=0
#### following config effects on FastDump ####
## when ldb_db_instance_count > 1, bucket will be sharded to instance base on config strategy.
## current supported:
## hash : just do integer hash to bucket number then module to instance, instance‘s balance may be
## not perfect in small buckets set. same bucket will be sharded to same instance
## all the time, so data will be reused even if buckets owned by server changed(maybe cluster has changed),
## map : handle to get better balance among all instances. same bucket may be sharded to different instance based
## on different buckets set(data will be migrated among instances).
ldb_bucket_index_to_instance_strategy=map
## bucket index can be updated. this is useful if the cluster wouldn‘t change once started
## even server down/up accidently.
ldb_bucket_index_can_update=1
## strategy map will save bucket index statistics into file, this is the file‘s directory
ldb_bucket_index_file_dir=/home/dataserver1/tair_bin/data/bindex
## memory usage for memtable sharded by bucket when batch-put(especially for FastDump)
ldb_max_mem_usage_for_memtable=3221225472
####
#### leveldb config (Warning: you should know what you‘re doing.)
## one leveldb instance max open files(actually table_cache_ capacity, consider as working set, see `ldb_table_cache_size)
ldb_max_open_files=655
## whether return fail when occure fail when init/load db, and
## if true, read data when compactiong will verify checksum
ldb_paranoid_check=0
## memtable size
ldb_write_buffer_size=67108864
## sstable size
ldb_target_file_size=8388608
## max file size in each level. level-n (n > 0): (n - 1) * 10 * ldb_base_level_size
ldb_base_level_size=134217728
## sstable‘s block size
# ldb_block_size=4096
## sstable cache size (override `ldb_max_open_files)
ldb_table_cache_size=1073741824
##block cache size
ldb_block_cache_size=16777216
## arena used by memtable, arena block size
#ldb_arenablock_size=4096
## key is prefix-compressed period in block,
## this is period length(how many keys will be prefix-compressed period)
# ldb_block_restart_interval=16
## specifid compression method (snappy only now)
# ldb_compression=1
## compact when sstables count in level-0 is over this trigger
ldb_l0_compaction_trigger=1
## write will slow down when sstables count in level-0 is over this trigger
## or sstables‘ filesize in level-0 is over trigger * ldb_write_buffer_size if ldb_l0_limit_write_with_count=0
ldb_l0_slowdown_write_trigger=32
## write will stop(wait until trigger down)
ldb_l0_stop_write_trigger=64
## when write memtable, max level to below maybe
ldb_max_memcompact_level=3
## read verify checksum
ldb_read_verify_checksums=0
## write sync log. (one write will sync log once, expensive)
ldb_write_sync=0
## bits per key when use bloom filter
#ldb_bloomfilter_bits_per_key=10
## filter data base logarithm. filterbasesize=1<<ldb_filter_base_logarithm
#ldb_filter_base_logarithm=12
该配置文件内容很多,红色标出来的是我修改的部分,其它的采用默认,其中:
(1)config_server的配置与之前必须完全相同。
(2)这里面的port和heartbeat_port是data server的端口号和心跳端口号,必须确保系统能给你使用这些端口号。一般默认的即可,这里我修改是因为自己的Linux系统只允许分配30000以后的端口号,根据自己情况修改。
(3)data文件、log文件等很重要,与前一样,最好用绝对路径
#group name
[group_1]
# data move is 1 means when some data serve down, the migrating will be start.
# default value is 0
_data_move=0
#_min_data_server_count: when data servers left in a group less than this value, config server will stop serve for this group
#default value is copy count.
_min_data_server_count=1
#_plugIns_list=libStaticPlugIn.so
_build_strategy=1 #1 normal 2 rack
_build_diff_ratio=0.6 #how much difference is allowd between different rack
# diff_ratio = |data_sever_count_in_rack1 - data_server_count_in_rack2| / max (data_sever_count_in_rack1, data_server_count_in_rack2)
# diff_ration must less than _build_diff_ratio
_pos_mask=65535 # 65535 is 0xffff this will be used to gernerate rack info. 64 bit serverId & _pos_mask is the rack info,
_copy_count=1
_bucket_number=1023
# accept ds strategy. 1 means accept ds automatically
_accept_strategy=1
# data center A
_server_list=10.10.7.146:51910
#_server_list=192.168.1.2:5191
#_server_list=192.168.1.3:5191
#_server_list=192.168.1.4:5191
# data center B
#_server_list=192.168.2.1:5191
#_server_list=192.168.2.2:5191
#_server_list=192.168.2.3:5191
#_server_list=192.168.2.4:5191
#quota info
_areaCapacity_list=0,1124000;
这个文件我只配置了data server列表,我只有一个dataserver,因此只需配置一个。
在完成安装配置之后, 可以启动集群了. 启动的时候需要先启动data server 然后再启动cofnig server. 如果是为已有的集群添加dataserver则可以先启动dataserver进程然后再修改gruop.conf,如果你先修改group.conf再启动进程,那么需要执行touch group.conf;在scripts目录下有一个脚本 tair.sh 可以用来帮助启动 tair.sh start_ds 用来启动data server. tair.sh start_cs 用来启动config server. 这个脚本比较简单, 它要求配置文件放在固定位置, 采用固定名称. 使用者可以通过执行安装目录下的bin下的 tair_server (data server) 和 tair_cfg_svr(config server) 来启动集群.
进入tair_bin目录后,按顺序启动:
sudo sbin/tair_server -f etc/dataserver.conf # 在config server端启动
sudo sbin/tair_cfg_svr -f etc/configserver.conf # 在data server端启动
执行启动命令后,在两端通过ps aux | grep tair查看是否启动了,这里启动起来只是第一步,还需要测试看是否真的启动成功,通过下面命令测试:
sudo sbin/tairclient -c 10.10.7.144:51980 -g group_1
TAIR> put k1 v1
put: success
TAIR> put k2 v2
put: success
TAIR> get k2
KEY: k2, LEN: 2
其中10.10.7.144:51980是config server IP:PORT,group_1是group name,在group.conf里配置的。
如果启动不成功或测试put/get时出现问题,那么需要查看config server端的logs/config.log和data server端的logs/server.log日志文件,里面会有具体的报错信息。
由于我的存储引擎选择的是ldb,而ldb有一个配置ldb_max_open_files=65535,即默认最多能打开的文件个数是65535个,但是我的系统不允许,可以通过“ulimit -n”查看系统运行程序中打开的最多文件个数,一般为1024个,远远小于65535,这时有两个办法来解决,一是修改ldb_max_open_files的值,使其小于1024;二是修改系统最多允许打开文件个数(下面的参考资料有提供修改的方法),由于我是测试使用,因此这里直接修改了ldb_max_open_files的值。[2014-07-09 10:37:24.863119] ERROR start (stat_manager.cpp:30) [139767832377088] open file [/home/dataserver1/tair_bin/data/ldb1/ldb/tair_db_001013.stat] failed: Too many open files[2014-07-09 10:37:24.863132] ERROR start (stat_manager.cpp:30) [139767832377088] open file [/home/dataserver1/tair_bin/data/ldb1/ldb/tair_db_001014.stat] failed: Too many open files[2014-07-09 10:37:24.863145] ERROR start (stat_manager.cpp:30) [139767832377088] open file [/home/dataserver1/tair_bin/data/ldb1/ldb/tair_db_001015.stat] failed: Too many open files[2014-07-09 10:37:24.863154] ERROR start (stat_manager.cpp:30) [139767832377088] open file [/home/dataserver1/tair_bin/data/ldb1/ldb/tair_db_001016.stat] failed: Too many open files[2014-07-09 10:37:24.863162] ERROR start (stat_manager.cpp:30) [139767832377088] open file [/home/dataserver1/tair_bin/data/ldb1/ldb/tair_db_001017.stat] failed: Too many open files
dataserver没配置好会报各种错误,下面列举一些我遇到的错误:
问题1:
TAIR> put abc aput: unknowTAIR> put a 11put: unknowTAIR> put abc 33put: unknowTAIR> get aget failed: data not exists.
问题2:
ERROR wakeup_wait_object (../../src/common/wait_object.hpp:302) [140627106383616] [3] packet is null
这些都是dataserver开始启动起来了,但是使用put/get时报错,然后dataserver马上down掉的情况,这时候就要根据log查看具体报错信息,修改错误的配置。
还有下面这样的报错信息:
[2014-07-09 09:08:11.646430] ERROR rebuild (group_info.cpp:879) [139740048353024] can not get enough data servers. need 1 lef 0
这是config server在启动时找不到data server,也就是data server必须要先启动成功后才能启动config server。
start tair_cfg_srv listen port 5199 error
有时候使用默认的端口号也不一定行,需要根据系统限制进行设置,比如我的系统环境只能运行普通用户使用30000以上的端口号,因此这里我就不能使用默认端口号了,改下即可。
Tair是一个分布式的key/value存储系统,数据往往存储在多个数据节点上。客户端需要决定数据存储的具体节点,然后才能完成具体的操作。
Tair的客户端通过和configserver交互获取这部分信息。configserver会维护一张表,这张表包含hash值与存储其对应数据的节点的对照关系。客户端在启动时,需要先和configserver通信,获取这张对照表。
在获取到对照表后,客户端便可以开始提供服务。客户端会根据请求的key的hash值,查找对照表中负责该数据的数据节点,然后通过和数据节点通信完成用户的请求。
Tair当前支持Java和c++语言的客户端。Java客户端已有相应的实现(可从这里下载到相应的jar包),我们直接使用封装的接口操作即可,但C++客户端目前还没看到实现版本(需要自己实现)。这里以简单的Java客户端为例进行客户端测试。
Java测试程序除了需要封装好的tair相关jar包之外,还需要tair依赖的一些jar包,具体的有下面几个(不一定是这个版本号):
commons-logging-1.1.3.jar
slf4j-api-1.7.7.jar
slf4j-log4j12-1.7.7.jar
log4j-1.2.17.jar
mina-core-1.1.7.jar
tair-client-2.3.1.jar
首先请参考Tair用户指南里面的关于java客户端的接口说明,下面直接给出示例,很容易理解。
package tair.client; import java.util.ArrayList; import java.util.List; import com.taobao.tair.DataEntry; import com.taobao.tair.Result; import com.taobao.tair.ResultCode; import com.taobao.tair.impl.DefaultTairManager; /** * @author WangJianmin * @date 2014-7-9 * @description Java-client test application for tair. * */ public class TairClientTest { public static void main(String[] args) { // 创建config server列表 List<String> confServers = new ArrayList<String>(); confServers.add("10.10.7.144:51980"); // confServers.add("10.10.7.144:51980"); // 可选 // 创建客户端实例 DefaultTairManager tairManager = new DefaultTairManager(); tairManager.setConfigServerList(confServers); // 设置组名 tairManager.setGroupName("group_1"); // 初始化客户端 tairManager.init(); // put 10 items for (int i = 0; i < 10; i++) { // 第一个参数是namespace,第二个是key,第三是value,第四个是版本,第五个是有效时间 ResultCode result = tairManager.put(0, "k" + i, "v" + i, 0, 10); System.out.println("put k" + i + ":" + result.isSuccess()); if (!result.isSuccess()) break; } // get one // 第一个参数是namespce,第二个是key Result<DataEntry> result = tairManager.get(0, "k3"); System.out.println("get:" + result.isSuccess()); if (result.isSuccess()) { DataEntry entry = result.getValue(); if (entry != null) { // 数据存在 System.out.println("value is " + entry.getValue().toString()); } else { // 数据不存在 System.out.println("this key doesn't exist."); } } else { // 异常处理 System.out.println(result.getRc().getMessage()); } } }
运行结果:
log4j:WARN No appenders could be found for logger (com.taobao.tair.impl.ConfigServer).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
put k0:true
put k1:true
put k2:true
put k3:true
put k4:true
put k5:true
put k6:true
put k7:true
put k8:true
put k9:true
get:true
value is v3
注意事项:测试如果不是在config server或data server上进行,那么一定要确保测试端系统与config server和data server能互相通信,即ping通。否则有可能会报下面这样的错误:
Exception in thread "main" java.lang.RuntimeException: init config failedat com.taobao.tair.impl.DefaultTairManager.init(DefaultTairManager.java:80)at tair.client.TairClientTest.main(TairClientTest.java:27)
我已将示例程序、需要的jar包及Makefile文件(我在Linux系统下测试,未用Eclipse跑程序)打包,需要的可以从这里下载。
2. Tair用户指南
淘宝分布式 key/value 存储引擎Tair安装部署过程及Java客户端测试一例,布布扣,bubuko.com
淘宝分布式 key/value 存储引擎Tair安装部署过程及Java客户端测试一例
原文:http://blog.csdn.net/lanxuezaipiao/article/details/37599151