文件夹
1. 简单介绍
2. 安装步骤及问题小记
3. 部署配置
4. Javaclient測试
5. 參考资料
声明
1. 以下的安装部署基于Linux系统环境:centos 6(64位),其他Linux版本号可能有所差异。
2. 网上有人说tair安装失败可能是由于gcc版本号问题,高版本号的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版本号无关,比方我的gcc開始版本号为4.4.7,后来tair安装失败,我又一次编译低版本号的gcc(gcc4.1.2)。可是问题相同出现。
后来发现是其他原因。修正后又一次用高版本号gcc4.4.7成功安装。
3. 以下的内容部分參考文档,转载请注明原文地址。
正文
1. 简单介绍
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 能够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 能够配置数据的备份数目, tair 自己主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之前须要先安装依赖库 tbsys 和 tbnet。
2.1.1 获取源代码
首先须要通过svn下载源代码,能够通过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之前须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上能够使用 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 # 同一时候会安装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. 环境变量设置 TBLIB_ROOT
取得源代码后, 先指定环境变量 TBLIB_ROOT 为须要安装的文件夹. 这个环境变量在兴许 tair 的编译安装中仍旧会被使用到.比方要安装到当前用户的lib文件夹下, 则指定export TBLIB_ROOT="~/lib"。b. 安装进入源代码文件夹, 执行build.sh进行安装.
- 2.1.4 编译安装tair
进入 tair 源代码文件夹,依次按以下顺序编译安装./bootstrap.sh./configure # 注意, 在执行configue的时候, 能够使用 --with-boost=xxxx 来指定boost的文件夹. 使用--with-release=yes 来编译release版本号.makemake install成功安装后会在当前用户home文件夹下生成文件夹tair_bin,即tair的成功安装后的文件夹。2.2 问题小记
安装过程并非一帆风顺的,期间出现了非常多问题,在此简单记录以供參考。2.2.1 g++未安装
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.说明安装了gcc但未安装g++,而tair是用C++开发的,因此仅仅能用g++编译。通过过 sudo yum install gcc-c++安装就可以。2.2.2 头文件路径错误
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 1由于tbnet和tbsys在两个不同的文件夹,但它们的源代码文件中头文件的互相引用却没有加绝对或相对路径,将两个文件夹的源代码加入到C++环境变量中就可以。have 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_PATH3. 部署配置
tair的执行, 至少须要一个 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。各自是对config server、data server及group信息的配置,在tair_bin安装文件夹下的etc文件夹下有这三个配置文件的样例,我们将其复制一下,成为我们须要的配置文件。cp configserver.conf.default configserver.confcp dataserver.conf.default dataserver.confcp 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细解释,以下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=10.10.7.144:51980config_server=10.10.7.144:51980[configserver]port=51980log_file=/home/dataserver1/tair_bin/logs/config.logpid_file=/home/dataserver1/tair_bin/logs/config.pidlog_level=warngroup_file=/home/dataserver1/tair_bin/etc/group.confdata_dir=/home/dataserver1/tair_bin/data/datadev_name=venet0:0注意事项:
(1)首先须要配置config server的服务器地址和端口号,端口号能够默认,服务器地址改成自己的,有一主一备两台configserver,这里仅为測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,并且是不对的相对路径(没有返回上级文件夹)。因此这里须要改动。注意data文件和log文件非常重要,data文件必不可少。而log文件是部署出错后能给你详细的出错原因。
(3)dev_name非常重要。须要设置为你自己当前网络接口的名称,默觉得eth0。这里我依据自己的网络情况进行了改动(ifconfig查看网络接口名称)。
3.2 配置data server
## tair 2.3 --- tairserver config #[public]config_server=10.10.7.144:51980config_server=10.10.7.144:51980[tairserver]##storage_engine:## mdb # kdb# ldb#storage_engine=ldblocal_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 portport=51910heartbeat_port=55910process_thread_num=16##mdb size in MB#slab_mem_size=1024log_file=/home/dataserver1/tair_bin/logs/server.logpid_file=/home/dataserver1/tair_bin/logs/server.pidlog_level=warndev_name=venet0:0ulog_dir=/home/dataserver1/tair_bin/data/ulogulog_file_number=3ulog_file_size=64check_expired_hour_range=2-4check_slab_hour_range=5-7dup_sync=1do_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 limitrsync_fail_log_size=30000000# whether do retry when rsync failed at first timersync_do_retry=0# when doing retry, size limit of retry log's memory usersync_retry_log_mem_size=100000000[fdb]# in MBindex_mmap_size=30cache_size=256bucket_size=10223free_block_pool_size=8data_dir=/home/dataserver1/tair_bin/data/fdbfdb_name=tair_fdb[kdb]# in bytemap_size=10485760 # the size of the internal memory-mapped regionbucket_size=1048583 # the number of buckets of the hash tablerecord_align=128 # the power of the alignment of record sizedata_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 instancesldb_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 allldb_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/countldb_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 blommfilterldb_use_bloomfilter=1## use mmap to speed up random acess file(sstable),may cost much memoryldb_use_mmap_random_access=0## how many highest levels to limit compactionldb_limit_compact_level_count=0## limit compaction ratio: allow doing one compaction every ldb_limit_compact_interval## 0 means limit all compactionldb_limit_compact_count_interval=0## limit compaction time interval## 0 means limit all compactionldb_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 compactionldb_limit_delete_obsolete_file_interval=5## whether trigger compaction by seekldb_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 directoryldb_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 checksumldb_paranoid_check=0## memtable sizeldb_write_buffer_size=67108864## sstable sizeldb_target_file_size=8388608## max file size in each level. level-n (n > 0): (n - 1) * 10 * ldb_base_level_sizeldb_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 sizeldb_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 triggerldb_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=0ldb_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 maybeldb_max_memcompact_level=3## read verify checksumldb_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<
该配置文件内容非常多,红色标出来的是我改动的部分。其他的採用默认。当中:
(1)config_server的配置与之前必须全然相同。
(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。一般默认的就可以。这里我改动是由于自己的Linux系统仅仅同意分配30000以后的端口号。依据自己情况改动。
(3)data文件、log文件等非常重要,与前一样,最好用绝对路径
3.3 配置group信息
#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;
这个文件我仅仅配置了data server列表,我仅仅有一个dataserver,因此仅仅需配置一个。
3.4 启动集群
在完毕安装配置之后, 能够启动集群了. 启动的时候须要先启动data server 然后再启动cofnig server. 假设是为已有的集群加入dataserver则能够先启动dataserver进程然后再改动gruop.conf,假设你先改动group.conf再启动进程,那么须要执行touch group.conf;在scripts文件夹下有一个脚本 tair.sh 能够用来帮助启动 tair.sh start_ds 用来启动data server. tair.sh start_cs 用来启动config server. 这个脚本比較简单, 它要求配置文件放在固定位置, 採用固定名称. 使用者能够通过执行安装文件夹下的bin下的 tair_server (data server) 和 tair_cfg_svr(config server) 来启动集群.
进入tair_bin文件夹后,按顺序启动:
sudo sbin/tair_server -f etc/dataserver.conf # 在dataserver端启动sudo sbin/tair_cfg_svr -f etc/configserver.conf # 在config 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。这里启动起来仅仅是第一步,还须要測试看是否真的启动成功。通过以下命令測试:
sudo sbin/tairclient -c 10.10.7.144:51980 -g group_1TAIR> put k1 v1 put: successTAIR> put k2 v2put: successTAIR> get k2KEY: k2, LEN: 2当中10.10.7.144:51980是config server IP:PORT,group_1是group name,在group.conf里配置的。
3.4 部署过程中的错误记录
假设启动不成功或測试put/get时出现故障,那么须要查看config server端的logs/config.log和data server端的logs/server.log日志文件,里面会有详细的报错信息。
3.4.1 Too many open files
3.4.2 data server问题
dataserver没配置好会报各种错误,以下列举一些我遇到的错误:
问题1:
问题2:
ERROR wakeup_wait_object (../../src/common/wait_object.hpp:302) [140627106383616] [3] packet is null 这些都是dataserver開始启动起来了。可是使用put/get时报错。然后dataserver立即down掉的情况,这时候就要依据log查看详细报错信息。改动错误的配置。还有以下这种报错信息:
[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干启动config server。
3.4.3 端口问题
start tair_cfg_srv listen port 5199 error有时候使用默认的端口号也不一定行。须要依据系统限制进行设置,比方我的系统环境仅仅能执行普通用户使用30000以上的端口号。因此这里我就不能使用默认端口号了,改下就可以。
4. Javaclient測试
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。
client须要决定数据存储的详细节点,然后才干完毕详细的操作。
Tair的client通过和configserver交互获取这部分信息。configserver会维护一张表,这张表包括hash值与存储其对应数据的节点的对比关系。
client在启动时,须要先和configserver通信,获取这张对比表。
在获取到对比表后,client便能够開始提供服务。client会依据请求的key的hash值,查找对比表中负责该数据的数据节点,然后通过和数据节点通信完毕用户的请求。
Tair当前支持Java和c++语言的client。Javaclient已有对应的实现(可从下载到对应的jar包),我们直接使用封装的接口操作就可以,但C++client眼下还没看到实现版本号(须要自己实现)。
这里以简单的Javaclient为例进行client測试。
4.1 依赖jar包
Java測试程序除了须要封装好的tair相关jar包之外,还须要tair依赖的一些jar包,详细的有以下几个(不一定是这个版本号号):
commons-logging-1.1.3.jarslf4j-api-1.7.7.jarslf4j-log4j12-1.7.7.jarlog4j-1.2.17.jarmina-core-1.1.7.jartair-client-2.3.1.jar
4.2 Javaclient程序
首先请參考里面的关于javaclient的接口说明,以下直接给出演示样例,非常easy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 ListconfServers = new ArrayList (); confServers.add("10.10.7.144:51980"); // confServers.add("10.10.7.144:51980"); // 可选 // 创建client实例 DefaultTairManager tairManager = new DefaultTairManager(); tairManager.setConfigServerList(confServers); // 设置组名 tairManager.setGroupName("group_1"); // 初始化client tairManager.init(); // put 10 items for (int i = 0; i < 10; i++) { // 第一个參数是namespace,第二个是key,第三是value,第四个是版本号。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 // 第一个參数是namespce。第二个是key Result 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()); } }}
执行结果:
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:trueput k1:trueput k2:trueput k3:trueput k4:trueput k5:trueput k6:trueput k7:trueput k8:trueput k9:trueget:truevalue is v3
注意事项:測试假设不是在config server或data server上进行,那么一定要确保測试端系统与config server和data server能互相通信,即ping通。否则有可能会报以下这种错误:
我已将演示样例程序、须要的jar包及Makefile文件(我在Linux系统下測试,未用Eclipse跑程序)打包,须要的能够从下载。
5. 參考资料
1.
2.
3.