一、前言

　　Tair支撑了淘宝几乎所有系统的缓存信息（Tair = Taobao Pair，Pair即Key-Value键值对），内置了三个存储引擎：mdb（默认，类似于Memcache）、rdb（类似于Redis）、ldb（高性能KV存储），其中前2者定位于cache缓存，ldb则定位于持久化存储。Tair属于分布式系统，由一个中心控制节点（Config Server）和一系列的服务节点（Data Server）组成，Config Server负责管理维护所有的Data Server状态信息。Data Server对外提供各种数据服务，并以心跳（Heartbeat）的形式将自身状况汇报给Config Server。Config Server是一个轻量级的控制点，可以采用Master-Slaver的形式来保证其可靠性，所有的Data Server地位都是等价的。持久化的数据存放于磁盘中，为了解决磁盘损坏导致的数据丢失, Tair可以配置数据的备份数目, 自动将一份数据的不同备份放到不同的主机上。

　　本文记录了详细的部署操作步骤（基于trunk版本），引用一张官方结构图，更多关于Tair的介绍请参照官方wiki（http://code.taobao.org/p/tair/wiki/intro/）。

二、安装Tair Server

　　1、系统环境：CentOS 6.5 （64位）

　　2、Tair Server 源码采用 C++ 编写，以下基于源码在linux环境下 make install

　　3、安装依赖包（感谢万能的yum）

　　　　1）wiki中描述需要安装依赖automake 、autoconfig、libtool库，实际CentOS6.5已经集成了以上lib，如果没有请通过yum获取

　　　　　　命令： “ yum install libtool ”

　　　　2）安装boost-devel库

　　　　　　命令： “ yum install boost-devel ”

　　　　3）安装gcc-c++

　　　　　　命令： “ yum install gcc-c++ ”

4、通过svn获取 tb-common-utils 和 Tair 源码

　　　　tb-common-utils 的 SVN地址：　　http://code.taobao.org/svn/tb-common-utils/trunk

　　　　Tair 的 SVN地址：　　http://code.taobao.org/svn/tair/trunk

　　5、将获取到的源码复制到当前用户目录，同时手工创建一个名称为“tairlib”文件夹，作为相关lib文件的安装路径，结构如下

　　6、安装tb-common-utils库，从命名可以看出应该是taobao内部开发的公共库

　　　　1）通过终端进入tb-common-utils文件夹，切换到root账号

　　　　2）给build.sh 脚本文件增加可执行X权限，否则可能会提示“权限不够”

　　　　　命令： “ chmod +x build.sh ”

　　　　3）创建环境变量TBLIB_ROOT指示相关lib文件的安装路径，指向之前创建的tairlib文件夹

　　　　　注意这个是会话级的变量，如果中间关闭终端需要重新export

　　　　　命令： export TBLIB_ROOT="/home/glf/tairlib"

　　　　4）执行build.sh脚本。

　　　　5）至此tb-common-utils库安装完毕。

　　7、安装tair

　　　　1）切换进入tair文件夹，如果是重新打开的终端窗口，请切换到root账号，同时参照6.3使用同样的命令创建环境变量，tair的安装同样需要这个环境变量

　　　　2）给bootstrap.sh 脚本文件增加可执行X权限，否则可能提示“权限不够"

　　　　　　命令： “ chmod +x bootstrap.sh ”

　　　　3）执行 bootstrap.sh 脚本

　　　　4）执行 configure

　　　　5）执行 make

　　　　6）执行 make install ，安装成功后会把tair安装到 /root/tair_bin ，至此安装tair 服务器完毕。

　　　　　因为使用的root账号安装，所以安装目录为/root，但如果使用当前用户在安装过程会提示权限问题，麻烦知道怎么解决的请告之。

三、Tair Server的配置

　　1、由于机器网络环境复杂，本文仅以一台机器不同端口号模拟分布式集群部署，如果多机器部署端口可以一致，只需要修改IP即可。

名称	IP	端口
Config Server（Master）	10.0.2.15	5198
Config Server（Slaver）	10.0.2.15	5200
Data Server A	10.0.2.15	5191
Data Server B	10.0.2.15	5192

　　　　关于IP、端口如何配置请参照下面的conf文件，但需要注意的是Config Server的心跳端口（Heartbeat Port）为Port+1，

　　　　例如Port=5198那么Heartbeat Port默认=5199，所以在配置其他端口的时候注意预留，不要重复。

　　2、CP 4份tair_bin文件夹，依次重命名如下图，后面都在4个CP的目录修改配置，原tair_bin保留不作任何修改（好不容易才装起来的呀：））。

　　　　tair_bin_cs1：作为Config Server（Master）目录

　　　　tair_bin_cs2：作为Config Server（Slaver）目录

　　　　tair_bin_ds1：作为Data Server A 目录

　　　　tair_bin_ds2：作为Data Server B 目录

　　3、依次在CP的4个目录下创建（mkdir） data 和 logs 文件夹，用于设置相关配置文件中的路径（不确定是否必须，也有可能服务启动的时候会根据conf设置的路径自动创建）

　　4、每个Server的etc 目录下都包含以下文件（安装时创建的sample文件），相关文件中已经存在对应的配置项解释说明，

　　　同时可以参照wiki的解释：http://code.taobao.org/p/tair/wiki/deploy

　　　 “configserver.conf.default” （Config Server使用）

　　　 “dataserver.conf.default” （Data Server使用）

　　　 “group.conf.default” （Config Server使用）

　　　 “invalserver.conf.default” （暂未使用）

　　5、配置Config Server

　　　　1）在 tair_bin_cs1 和 tair_bin_cs2 的etc目录下将 “configserver.conf.default” 重命名为“configserver.conf”，将“group.conf.default”重命名为“group.conf”，作为服务器的正式配置文件。

　　　　2）打开 tair_bin_cs1\etc\configserver.conf 参照如下代码进行配置，其中第一行config_server为master服务器，第二行为slaver服务器，

　　　　　使用绝对路径修改 log_file、pid_file、goup_file、data_dir 目录，使用 ifconfig 命名查看当前网卡的dev_name和ip，以下修改过的内容用红色字体标识。

　　　　　（插曲：因为dev_name默认为eth0，我机器实际为eth1，一度陷入了绝境）

#

# tair 2.3 --- configserver config

#

[public]

config_server=10.0.2.15:5198

config_server=10.0.2.15:5200

[configserver]

port=5198

log_file=/root/tair_bin_cs1/logs/config.log

pid_file=/root/tair_bin_cs1/logs/config.pid

log_level=warn

group_file=/root/tair_bin_cs1/etc/group.conf

data_dir=/root/tair_bin_cs1/data/data

dev_name=eth1

　　　　3）在 tair_bin_cs1\etc\group.conf 参照如下代码进行配置，主要用于注册DataSever服务器的IP和Port

#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=10.0.2.15:5191

_server_list=10.0.2.15:5192

#quota info

_areaCapacity_list=0,1124000;

　　　　4）Config Server（Slave）的配置也基本一致，注意修改conf文件中的路径、ip

　　　　　 configserver.conf 参照如下：

#

# tair 2.3 --- configserver config

#

[public]

config_server=10.0.2.15:5198

config_server=10.0.2.15:5200

[configserver]

port=5200

log_file=/root/tair_bin_cs2/logs/config.log

pid_file=/root/tair_bin_cs2/logs/config.pid

log_level=warn

group_file=/root/tair_bin_cs2/etc/group.conf

data_dir=/root/tair_bin_cs2/data/data

dev_name=eth1

　　　　　 group.conf 参照如下：

#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=10.0.2.15:5191

_server_list=10.0.2.15:5192 

#quota info

_areaCapacity_list=0,1124000;

　　　　5）至此2台 Config Server 配置完毕

　　6、配置Data Server（默认为 mdb 引擎）

　　　　1）在2个Data Server的 etc 目录下将 “dataserver.conf.default” 重命名为“dataserver.conf”，作为服务器的正式配置文件

　　　　2）打开 tair_bin_ds1\etc\dataserver.conf 参照如下代码进行修改配置，注意[public]节点的2行config_server必须和configserver上的配置保持一致

#

#  tair 2.3 --- tairserver config

#

[public]

config_server=10.0.2.15:5198

config_server=10.0.2.15:5200

[tairserver]

#

#storage_engine:

#

# mdb

# kdb

# ldb

#

storage_engine=mdb

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=5191

heartbeat_port=6191

process_thread_num=16

#

#mdb size in MB

#

slab_mem_size=1024

log_file=/root/tair_bin_ds1/logs/server.log

pid_file=/root/tair_bin_ds1/logs/server.pid

log_level=warn

dev_name=eth1

ulog_dir=/root/tair_bin_ds1/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=/root/tair_bin_ds1/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=/root/tair_bin_ds1/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=/root/tair_bin_ds1/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=/root/tair_bin_ds1/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=/root/tair_bin_ds1/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=65535

## 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

　　　　3）另一台DataServer的配置基本一致，参照如下代码

　　　　　注意：由于属于单机部署多个DataServer，需要修改mdb_shm_path=/mdb_shm_path02，（ps：这点我开始没留意导致每次启动一个dataserver的时候另一台自动shutdown）

#

#  tair 2.3 --- tairserver config

#

[public]

config_server=10.0.2.15:5198

config_server=10.0.2.15:5200

[tairserver]

#

#storage_engine:

#

# mdb

# kdb

# ldb

#

storage_engine=mdb

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_path02

#tairserver listen port

port=5192

heartbeat_port=6192

process_thread_num=16

#

#mdb size in MB

#

slab_mem_size=1024

log_file=/root/tair_bin_ds2/logs/server.log

pid_file=/root/tair_bin_ds2/logs/server.pid

log_level=warn

dev_name=eth1

ulog_dir=/root/tair_bin_ds2/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=/root/tair_bin_ds2/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=/root/tair_bin_ds2/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=/root/tair_bin_ds2/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=/root/tair_bin_ds2/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=/root/tair_bin_ds2/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=65535

## 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

　　　　4）至此2台 Data Server 也配置完毕

四、启动Tair Server集群

　　1、通过终端任意选其中一台Server执行 set_shm.sh（需要root权限），修改系统分配内存策略，确保程序能够使用足够的共享内存

　　　　命令： “ ./set_shm.sh ”

　　2、分别通过终端进入2台Data Server目录，执行 tair.sh 脚本启动服务器，注意：请先启动DataServer，后启动ConfigServer，相关解释见wiki

　　　　此时由于Config Server还没有启动，Log会出现heartbeat错误。

[2014-12-19 19:28:42.336703] ERROR handlePacket (heartbeat_thread.cpp:141) [140335215126272] ControlPacket, cmd:3

[2014-12-19 19:28:43.341952] ERROR handlePacket (heartbeat_thread.cpp:141) [140335215126272] ControlPacket, cmd:2

[2014-12-19 19:28:43.341982] ERROR handlePacket (heartbeat_thread.cpp:141) [140335215126272] ControlPacket, cmd:3

[2014-12-19 19:28:44.345308] WARN  update_server_table (tair_manager.cpp:1397) [140334767929088] updateServerTable, size: 2046

[2014-12-19 19:28:44.345312] WARN  handlePacket (heartbeat_thread.cpp:212) [140335215126272] config server HOST UP: 10.0.2.15:5198

[2014-12-19 19:28:44.345350] WARN  handlePacket (heartbeat_thread.cpp:212) [140335215126272] config server HOST UP: 10.0.2.15:5200

　　　　命令： “ ./tair.sh start_ds ”

　　3、分别通过终端进入2台Config Server目录，通过执行 tair.sh 脚本来启动服务器

　　　　命令： “ ./tair.sh start_cs ”

　　4、至此4台服务器启动完毕，过程不会一帆风顺，请耐心仔细，查阅log文件

五、客户端连接Tair Server

　　1、连接Tair服务器目前有3种方式：命令行、C++版本TairClient、Java版本TairClient（从依赖包可以看出使用的Mina通信框架），

　　　　底层使用socket通信，所以理论上只要支持socket操作的程序语言都可以直接实现Tair客户端

　　2、通过终端进入任意一个Server程序目录的 sbin 文件夹，执行 tairclient 命令连接Tair服务器，-c参数表示连接configserver，-s参数表示连接dataserver，

　　　　参照下图命令连接，“group_1” 是group.conf配置文件中的默认值。

　　　　连接到 tair configserver 后可以通过 put命令新增一个键值对，例如：put key1 hellowold，然后通过get命令取值，如下图：

　　　　也可以连接到tair dataserver后可以查看单独某个ds上的数据，下图可以看出当连接到Port=5191的DataServer可以取到key1的值，5192的DS上则不能取到值。

　　　　Tair ConfigServer负载均衡采用一致性哈希算法进行数据分配，更多相关内容请查阅wiki。

六、更多

　　至此Tair服务器安装部署完毕，更多关于学习、整合、测试相关的内容请期待后续博文，同时也欢迎有兴趣的人交流沟通。

巴特西

基于淘宝开源Tair分布式KV存储引擎的整合部署

一、前言

二、安装Tair Server

三、Tair Server的配置

四、启动Tair Server集群

五、客户端连接Tair Server

六、更多

七、向开源工作者和组织致敬，@tair team，感谢对开源事业作出的任何贡献

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