黄东旭解析 TiDB 的核心优势
749
2023-04-10
在阅读关于 PD Control 工具使用的文档时,发现文档未对 --jq 格式化选项的语法作太多详细介绍。于是,诞生了本文档,希望对如我这种新手小白有一定的帮助
在介绍 pd-ctl 的命令行选项 --jq之前,首先了解一下 Linux 中的命令行工具 jq。jq 是一个命令行的 JSON 文本格式化工具。jq 将给定的 Filter(过滤器)应用于其输入的 JSON 文本中,并将执行结果以 JSON 格式返回到标准输出中。
官方文档链接:https://stedolan.github.io/jq/manual/
首先,准备 2 份测试文件。文件1(jsonstr.txt)内容为一段未格式化的 JSON 字符串;文件2(jsonfmt.txt)内容为一段格式化后的 JSON 文本。
~]$ cat > jsonstr.txt << EOF {"Skills": ["***", "Python", "MySQL", "Latex"], "Age": 38, "Birthday": "19th Jan", "Name": "Jack", "Email": "Jack@outlook.com", "Education":{"University":"LNTU","College":"Electronics & Information Engineering","Professonal":"Computer Science & Technology","Year":"2007"}} EOF{ "count": 3, "stores": [ { "store": { "id": 1, "address": "192.168.3.225:20160", "version": "6.1.0", "status_address": "192.168.3.225:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078152, "deploy_path": "/TiDB-deploy/tikv-20160/bin", "last_heartbeat": 1660965837130921869, "state_name": "Up" }, "status": { "capacity": "19.56GiB", "available": "15.7GiB", "used_size": "1.01GiB", "leader_count": 6, "leader_weight": 1, "leader_score": 6, "leader_size": 417, "region_count": 22, "region_weight": 1, "region_score": 6859819744.928351, "region_size": 1811, "slow_score": 1, "start_ts": "2022-07-29T15:02:32+08:00", "last_heartbeat_ts": "2022-08-20T11:23:57.130921869+08:00", "uptime": "524h21m25.130921869s" } }, { "store": { "id": 4, "address": "192.168.3.224:20160", "version": "6.1.0", "status_address": "192.168.3.224:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078147, "deploy_path": "/tidb-deploy/tikv-20160/bin", "last_heartbeat": 1660965841338055613, "state_name": "Up" }, "status": { "capacity": "19.56GiB", "available": "15.69GiB", "used_size": "1.011GiB", "leader_count": 11, "leader_weight": 1, "leader_score": 11, "leader_size": 932, "region_count": 22, "region_weight": 1, "region_score": 6861359887.412361, "region_size": 1811, "slow_score": 1, "start_ts": "2022-07-29T15:02:27+08:00", "last_heartbeat_ts": "2022-08-20T11:24:01.338055613+08:00", "uptime": "524h21m34.338055613s" } }, { "store": { "id": 5, "address": "192.168.3.226:20160", "version": "6.1.0", "status_address": "192.168.3.226:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078162, "deploy_path": "/tidb-deploy/tikv-20160/bin", "last_heartbeat": 1660965837041716427, "state_name": "Up" }, "status": { "capacity": "19.56GiB", "available": "15.69GiB", "used_size": "1.031GiB", "leader_count": 5, "leader_weight": 1, "leader_score": 5, "leader_size": 462, "region_count": 22, "region_weight": 1, "region_score": 6862644983.297757, "region_size": 1811, "slow_score": 1, "start_ts": "2022-07-29T15:02:42+08:00", "last_heartbeat_ts": "2022-08-20T11:23:57.041716427+08:00", "uptime": "524h21m15.041716427s" } } ] }【注意】该测试文本为一个 TiDB 集群数据库中的 store 信息。可通过如下方式获取类似格式的 JSON 文本。
~]$ tiup ctl:v6.1.0 pd -u http://192.168.3.221:2379 store > jsonfmt.txt其中 http://192.168.3.221:2379 为 PD 实例的地址,获取的json信息通过>重定向输入到jsonfmt.txt。
1.3.2.2. JSON 字符串格式化直接通过 jq 命令,格式化文本
~]$ jq --tab -S . jsonstr.txt { "Skills": [ "1.***", "2.Python", "3.MySQL", "4.Latex" ], "Age": 38, "Birthday": "19th Jan", "Name": "Jack", "Email": "Jack@outlook.com", "Education": { "University": "LNTU", "College": "Electronics & Information Engineering", "Professonal": "Computer Science & Technology", "Year": "2007" } }这里的过滤器.,表示只对输入的内容做 JSON 格式化,而不修改其内容,效果与下面的过滤器 values 一致。
~]$ cat jsonstr.txt | jq values { "Skills": [ "1.***", "2.Python", "3.MySQL", "4.Latex" ], "Age": 38, "Birthday": "19th Jan", "Name": "Jack", "Email": "Jack@outlook.com", "Education": { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" } }通过管道符调用 jq,格式化文本
~]$ cat jsonstr.txt | jq --tab -S . { "Age": 38, "Birthday": "19th Jan", "Education": { "College": "Electronics & Information Engineering", "Professonal": "Computer Science & Technology", "University": "LNTU", "Year": "2007" }, "Email": "Jack@outlook.com", "Name": "Jack", "Skills": [ "1.***", "2.Python", "3.MySQL", "4.Latex" ] }默认的缩进为 2 个空格,--tab 表示将缩进替换为 tab 制表符;-S 表示对格式化后的 JSON 文本按 KEY 排序。
【注意】为简化描述,避免文档过于冗长,后续示例均以管道方式来描述 jq 的使用。
1.3.2.3. 以列表形式获取 Key(只能获取 1 级的 Key 信息)~]$ cat jsonstr.txt | jq keys [ "Age", "Birthday", "Education", "Email", "Name", "Skills" ]这里的 keys 为关键字
1.3.2.4. 提取指定 Key 的 Value(Key Filter)jq .Key1名称, .Key2名称, ...获取某个 Key 的 Value
当 JSON 文本过长,只想提取其中某个 Key 的 Value。可通过如下语法完成。
~]$ jq .Education jsonstr.txt { "University": "LNTU", "College": "Electronics & Information Engineering", "Professonal": "Computer Science & Technology", "Year": "2007" } ~]$ cat jsonstr.txt |jq .Education { "University": "LNTU", "College": "Electronics & Information Engineering", "Professonal": "Computer Science & Technology", "Year": "2007" }获取某几个 Key 的 Value
逗号分隔多个 Key,可获取指定的多个 Key 的 Value。
~]$ cat jsonstr.txt | jq .Education, .Skills { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" } [ "1.***", "2.Python", "3.MySQL", "4.Latex" ]1.3.2.5. 提取指定 Key 的 KV(Key-Value Filter)jq {Key1名称}, {Key2名称}, ...获取某个 Key 的 KV
~]$ cat jsonstr.txt | jq {Education} { "Education": { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" } }获取多个 Key 的 KV
~]$ cat jsonstr.txt | jq {Education}, {Skills} { "Education": { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" } } { "Skills": [ "1.***", "2.Python", "3.MySQL", "4.Latex" ] }1.3.2.6. 通过 ‘.<Key名称>[]’ 递归指定 Key 下的 Value 信息递归获取 1 级的所有 Value
不指定 Key 名称时,则获取 1 级的 Value 信息
~]$ cat jsonstr.txt | jq .[] [ "1.***", "2.Python", "3.MySQL", "4.Latex" ] 38 "19th Jan" "Jack" "Jack@outlook.com" { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" }获取 Education下的所有 Value 信息
指定 Key 名称时,则获取指定 Key 下的所有 Value 信息
~]$ cat jsonstr.txt | jq .Education[] "LNTU" "Electronics & Information Engineering" "Computer Science & Technology" "2007"注意过滤器 .Education[] 与 .Education 的区别。
~]$ cat jsonstr.txt | jq .Education { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" }1.3.2.7. 通过 select 检索包含指定 KV 的内容# 通过 .stores[] 递归取出 stores 中每个元素(元素中包含store和status两部分内容); # 再通过 .store 过滤出每个元素中的 store 部分的内容。 ~]$ cat jsonfmt.txt | jq .stores[].store { "id": 1, "address": "192.168.3.225:20160", "version": "6.1.0", "status_address": "192.168.3.225:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078152, "deploy_path": "/tidb-deploy/tikv-20160/bin", "last_heartbeat": 1660966497198077000, "state_name": "Up" } { "id": 4, "address": "192.168.3.224:20160", "version": "6.1.0", "status_address": "192.168.3.224:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078147, "deploy_path": "/tidb-deploy/tikv-20160/bin", "last_heartbeat": 1660966491404376800, "state_name": "Up" } { "id": 5, "address": "192.168.3.226:20160", "version": "6.1.0", "status_address": "192.168.3.226:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078162, "deploy_path": "/tidb-deploy/tikv-20160/bin", "last_heartbeat": 1660966497108902000, "state_name": "Up" } # 通过 .stores[].store 过滤出多个 store # 对多个 store 应用 select 条件(id ==5)查询,筛选出包含 id == 5 的 store。 ~]$ cat jsonfmt.txt | jq .stores[].store | select(.id == 5) { "id": 5, "address": "192.168.3.226:20160", "version": "6.1.0", "status_address": "192.168.3.226:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078162, "deploy_path": "/tidb-deploy/tikv-20160/bin", "last_heartbeat": 1660966497108902000, "state_name": "Up" }1.3.2.8. 列表中的元素提取或切片(Index Filter)当某个 Key 对应的 Value 是一个列表时,jq 可通过如下语法对 Value 进行元素提取或切片。
列表中单个元素的提取
jq .Key名称[元素下标,元素下标,,]~]$ cat jsonstr.txt | jq .Skills[] "1.***" "2.Python" "3.MySQL" "4.Latex" ~]$ cat jsonstr.txt | jq .Skills[0] "1.***" ~]$ cat jsonstr.txt | jq .Skills[1] "2.Python" ~]$ cat jsonstr.txt | jq .Skills[-2] "3.MySQL" ~]$ cat jsonstr.txt | jq .Skills[1,3] "2.Python" "4.Latex"列表中连续多个元素的切片
jq .Key名称[起始下标:结束下标(不含)][切片起始下标:切片结束下标(不含)] 切片区间是一个左闭右开的区间,即[起始下标, 结束下标),并且 结束下标 需大于 起始下标。如 [1,3] 表示提取下标为 1 至 3,但不包含 3 的元素。
当下标为负数时,表示从末尾反向计算下标。倒数第1个元素下标为-1,倒数第2个为 -2 依次类推。
~]$ cat jsonstr.txt | jq .Skills[0] "1.***" ~]$ cat jsonstr.txt | jq .Skills[0:1] [ "1.***" ] ~]$ cat jsonstr.txt | jq .Skills[0:2] [ "1.***", "2.Python" ] ~]$ cat jsonstr.txt | jq .Skills[1:10] [ "2.Python", "3.MySQL", "4.Latex" ] ~]$ cat jsonstr.txt | jq .Skills[-2,3] "3.MySQL" "4.Latex" ~]$ cat jsonstr.txt | jq .Skills[-2:1] []注意与 Python 列表切片的区别
1.3.2.9. 管道嵌套利用管道符,计算每个 Key 的 Value 长度
~]$ cat jsonstr.txt | jq .Education { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" } ~]$ cat jsonstr.txt | jq .Education | length 4length 过滤器,计算元素长度。对于对象,表示对象里的元素个数;对于字符串,表示字符串字符数;对于列表,表示列表元素个数。
利用管道符,逐级过滤
~]$ cat jsonstr.txt | jq .Education | .College "Electronics & Information Engineering"1.3.2.10. 递归展开所有层级的 KV~]$ cat jsonstr.txt | jq .. { "Skills": [ "1.***", "2.Python", "3.MySQL", "4.Latex" ], "Age": 38, "Birthday": "19th Jan", "Name": "Jack", "Email": "Jack@outlook.com", "Education": { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" } } [ "1.***", "2.Python", "3.MySQL", "4.Latex" ] "1.***" "2.Python" "3.MySQL" "4.Latex" 38 "19th Jan" "Jack" "Jack@outlook.com" { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" } "LNTU" "Electronics & Information Engineering" "Computer Science & Technology" "2007"1.3.2.11. map 或 map_value 列表遍历通过 map 遍历每个 KEY,并应用 length 计算每个 Key 对应的 Value 长度
针对对象,计算其元素个数;针对字符串计算其字符串长度。
~]$ cat jsonstr.txt | jq map(. | length) [ 4, 38, 8, 4, 16, 4 ]1.3.2.12. 重构 JSON([]与{})用各种 Filter 格式化后的 JSON 内容,可通过 [] 和 {} 来重新组织,生成新的 JSON 文本。
~]$ cat jsonstr.txt | jq .Education, .Skills { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" } [ "1.***", "2.Python", "3.MySQL", "4.Latex" ]利用 [],将输出重新组织成列表
~]$ cat jsonstr.txt | jq [.Education, .Skills] [ { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" }, [ "1.***", "2.Python", "3.MySQL", "4.Latex" ] ]利用 {},将输出重新组织成 JSON 对象
~]$ cat jsonstr.txt | jq {Education, Skills} { "Education": { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" }, "Skills": [ "1.***", "2.Python", "3.MySQL", "4.Latex" ] }利用 {},重构 JSON对象,并指定新的 Key 名称。
~]$ cat jsonstr.txt | jq {EducationDetail: .Education, SkillInfo: .Skills} { "EducationDetail": { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" }, "SkillInfo": [ "1.***", "2.Python", "3.MySQL", "4.Latex" ] }~]$ cat jsonstr.txt | jq {EducationDetail: {Education}, SkillInfo: {Skills}} { "EducationDetail": { "Education": { "University": "LNTU", "College": "Electronics & Information Engineering", "Professnal": "Computer Science & Technology", "Year": "2007" } }, "SkillInfo": { "Skills": [ "1.***", "2.Python", "3.MySQL", "4.Latex" ] } }了解 jq 的常见使用方式后,便可通过如下三种方式,格式化输出 PD 的配置信息:
在使用 pd-ctl 工具时指定 --jq <过滤器> 来格式化 PD 配置信息的输出。--jq 本质上也是调用系统中的 jq 工具,来执行格式化输出。因此,其该参数的语法与 jq 完全一致。
可利用管道符|,将 PD 配置信息的内容重定向到 jq 命令,作格式化输出。
混合使用 pd-ctl 的 --jq 选项与 jq 命令。
【注意】因 pd-ctl 的 --jq选项本质上就是调用系统中的 jq 命令,因此系统中需要安装 jq 工具包。
格式化显示完整的 PD 调度信息
~]$ export PD_ADDR=http://192.168.3.222:2379 ~]$ tiup ctl:v6.1.0 pd config show Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd config show { "replication": { "enable-placement-rules": "true", "enable-placement-rules-cache": "false", "isolation-level": "", "location-labels": "", "max-replicas": 3, "strictly-match-label": "false" }, "schedule": { "enable-cross-table-merge": "true", "enable-joint-consensus": "true", "high-space-ratio": 0.7, "hot-region-cache-hits-threshold": 3, "hot-region-schedule-limit": 4, "hot-regions-reserved-days": 0, "hot-regions-write-interval": "10m0s", "leader-schedule-limit": 4, "leader-schedule-policy": "count", "low-space-ratio": 0.8, "max-merge-region-keys": 200000, "max-merge-region-size": 20, "max-pending-peer-count": 64, "max-snapshot-count": 64, "max-store-down-time": "30m0s", "max-store-preparing-time": "48h0m0s", "merge-schedule-limit": 8, "patrol-region-interval": "10ms", "region-schedule-limit": 2048, "region-score-formula-version": "v2", "replica-schedule-limit": 64, "split-merge-interval": "1h0m0s", "tolerant-size-ratio": 0 } }格式化显示完整的 Store 信息
~]$ tiup ctl:v6.1.0 pd store Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd store { "count": 3, "stores": [ { "store": { "id": 1, "address": "192.168.3.225:20160", "version": "6.1.0", "status_address": "192.168.3.225:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078152, "deploy_path": "/tidb-deploy/tikv-20160/bin", "last_heartbeat": 1660978688453748544, "state_name": "Up" }, "status": { "capacity": "19.56GiB", "available": "15.7GiB", "used_size": "1.011GiB", "leader_count": 6, "leader_weight": 1, "leader_score": 6, "leader_size": 417, "region_count": 22, "region_weight": 1, "region_score": 6860013051.732055, "region_size": 1811, "slow_score": 1, "start_ts": "2022-07-29T15:02:32+08:00", "last_heartbeat_ts": "2022-08-20T14:58:08.453748544+08:00", "uptime": "527h55m36.453748544s" } }, { "store": { "id": 4, "address": "192.168.3.224:20160", "version": "6.1.0", "status_address": "192.168.3.224:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078147, "deploy_path": "/tidb-deploy/tikv-20160/bin", "last_heartbeat": 1660978692660915975, "state_name": "Up" }, "status": { "capacity": "19.56GiB", "available": "15.69GiB", "used_size": "1.011GiB", "leader_count": 11, "leader_weight": 1, "leader_score": 11, "leader_size": 932, "region_count": 22, "region_weight": 1, "region_score": 6861560216.947071, "region_size": 1811, "slow_score": 1, "start_ts": "2022-07-29T15:02:27+08:00", "last_heartbeat_ts": "2022-08-20T14:58:12.660915975+08:00", "uptime": "527h55m45.660915975s" } }, { "store": { "id": 5, "address": "192.168.3.226:20160", "version": "6.1.0", "status_address": "192.168.3.226:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078162, "deploy_path": "/tidb-deploy/tikv-20160/bin", "last_heartbeat": 1660978688364585582, "state_name": "Up" }, "status": { "capacity": "19.56GiB", "available": "15.69GiB", "used_size": "1.031GiB", "leader_count": 5, "leader_weight": 1, "leader_score": 5, "leader_size": 462, "region_count": 22, "region_weight": 1, "region_score": 6862846131.837539, "region_size": 1811, "slow_score": 1, "start_ts": "2022-07-29T15:02:42+08:00", "last_heartbeat_ts": "2022-08-20T14:58:08.364585582+08:00", "uptime": "527h55m26.364585582s" } } ] }格式化显示完整的 Region 信息
~]$ tiup ctl:v6.1.0 pd region | jq . Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd region { "count": 22, "regions": [ { "id": 172, "start_key": "7480000000000000FF5C00000000000000F8", "end_key": "7480000000000000FF5E00000000000000F8", "epoch": { "conf_ver": 47, "version": 68 }, "peers": [ { "id": 173, "store_id": 1, "role_name": "Voter" }, { "id": 4467, "store_id": 4, "role_name": "Voter" }, { "id": 4497, "store_id": 5, "role_name": "Voter" } ], "leader": { "id": 4467, "store_id": 4, "role_name": "Voter" }, "written_bytes": 0, "read_bytes": 0, "written_keys": 0, "read_keys": 0, "approximate_size": 85, "approximate_keys": 1079434 }, ...... ] }通过 KV Filter 过滤出 store 与 status 完整信息
~]$ tiup ctl:v6.1.0 pd store --jq=".stores[]" |jq {store}, {status} Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd store --jq=.stores[] { "store": { "id": 4, "address": "192.168.3.224:20160", "version": "6.1.0", "status_address": "192.168.3.224:20180", "git_hash": "080d086832ae5ce2495352dccaf8df5d40f30687", "start_timestamp": 1659078147, "deploy_path": "/tidb-deploy/tikv-20160/bin", "last_heartbeat": 1660980592856686300, "state_name": "Up" } } { "status": { "capacity": "19.56GiB", "available": "15.69GiB", "used_size": "1.012GiB", "leader_count": 11, "leader_weight": 1, "leader_score": 11, "leader_size": 932, "region_count": 22, "region_weight": 1, "region_score": 6861587385.861746, "region_size": 1811, "slow_score": 1, "start_ts": "2022-07-29T15:02:27+08:00", "last_heartbeat_ts": "2022-08-20T15:29:52.856686305+08:00", "uptime": "528h27m25.856686305s" } } ......筛选字段,重构 JSON 文本
首先,通过 KV Filter 筛选出 store.id、store.address、store.state_name、status.available 字段;再通过 {} 重构 JSON 内容,重构时指定新的 KEY 字段名称。
~]$ tiup ctl:v6.1.0 pd store --jq=".stores[]" |jq {store_id: .store.id, addr: .store.address, state: .store.state_name, freespace: .status.available} Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd store --jq=.stores[] { "store_id": 1, "addr": "192.168.3.225:20160", "state": "Up", "freespace": "15.7GiB" } { "store_id": 4, "addr": "192.168.3.224:20160", "state": "Up", "freespace": "15.69GiB" } { "store_id": 5, "addr": "192.168.3.226:20160", "state": "Up", "freespace": "15.69GiB" }2.2.2.2. 按序查询状态为 Down 的 Store 信息~]$ tiup ctl:v6.1.0 pd store --jq=".stores[]" |jq {store_id: .store.id, addr: .store.address, state: .store.state_name, freespace: .status.available} | jq . | select(.state="Up")2.2.2.3. 查询 TiKV 的信息判断 Store 为 TiKV 的依据为 “如果 Store 的部署目录为 /tidb-deploy/tikv-20160/bin,则可断定其为 TiKV”。依据的前提是,各组件均规范化部署。
~]$ tiup ctl:v6.1.0 pd store --jq=".stores[]" |jq {store_id: .store.id, addr: .store.address, state: .store.state_name, path: .store.deploy_path, freespace: .status.available} |jq . |select(.path == "/tidb-deploy/tikv-20160/bin") Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd store --jq=.stores[] { "store_id": 1, "addr": "192.168.3.225:20160", "state": "Up", "path": "/tidb-deploy/tikv-20160/bin", "freespace": "15.7GiB" } { "store_id": 4, "addr": "192.168.3.224:20160", "state": "Up", "path": "/tidb-deploy/tikv-20160/bin", "freespace": "15.69GiB" } { "store_id": 5, "addr": "192.168.3.226:20160", "state": "Up", "path": "/tidb-deploy/tikv-20160/bin", "freespace": "15.69GiB" }查看 Region 分布情况,包括 Region ID、副本分布、Leader分布
~]$ tiup ctl:v6.1.0 pd region | jq .regions[] | {region_id: .id, peer_stores: [.peers[].store_id], leader_store: .leader.store_id} Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd region { "region_id": 192, "peer_stores": [ 1, 5, 4 ], "leader_store": 4 } { "region_id": 244, "peer_stores": [ 5, 1, 4 ], "leader_store": 5 } ......查看 Region 分布情况,包括 Region ID、起始Key值、副本分布、Leader分布
~]$ tiup ctl:v6.1.0 pd region | jq .regions[] | {region_id: .id, key: [.start_key,.end_key], peer_stores: [.peers[].store_id], leader_store: .leader.store_id} Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd region { "region_id": 196, "key": [ "7480000000000000FF645F728000000000FF04F8C70000000000FA", "7480000000000000FF645F728000000000FF0630A00000000000FA" ], "peer_stores": [ 1, 4, 5 ], "leader_store": 4 } { "region_id": 204, "key": [ "7480000000000000FF645F728000000000FF09CDB50000000000FA", "7480000000000000FF645F728000000000FF0D6E840000000000FA" ], "peer_stores": [ 5, 4, 1 ], "leader_store": 4 } ......2.2.3.2. 根据 Region 副本数,过滤 Region查找副本数不等于3的Region
~]$ tiup ctl:v6.1.0 pd region --jq=".regions[]" | jq {region_id: .id, peer_stores: [.peers[].store_id] | select(length != 3)} Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd region --jq=.regions[] { "region_id": 252, "peer_stores": [ 4, 5 ] } { "region_id": 216, "peer_stores": [ 1, 4 ] }2.2.3.3. 查询指定 Store 上的 Region查看 Store ID 为 4 上的 Region。
~]$ tiup ctl:v6.1.0 pd region |jq .regions[] | {region_id: .id, peer_stores: [.peers[].store_id] | select(any(.==4))} Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd region { "region_id": 252, "peer_stores": [ 1, 4, 5 ] } { "region_id": 216, "peer_stores": [ 5, 1, 4 ] } ......~]$ tiup ctl:v6.1.0 pd region |jq .regions[] | {region_id: .id, peer_stores: [.peers[].store_id] | select(any(.==(1,4)))}2.2.3.4. 查询指定 Store 上的 Leader查询指定 Store 上的 Leade,以及该 Leader 的其他副本分布情况。
~]$ tiup ctl:v6.1.0 pd region | jq .regions[] | select(.leader.store_id == 1) | {region_id: .id, peer_stores: [.peers[].store_id]} Starting component `ctl`: /home/tidb/.tiup/components/ctl/v6.1.0/ctl pd region { "region_id": 200, "peer_stores": [ 5, 4, 1 ] } { "region_id": 180, "peer_stores": [ 5, 4, 1 ] }版权声明:本文内容由网络用户投稿,版权归原作者所有,本站不拥有其著作权,亦不承担相应法律责任。如果您发现本站中有涉嫌抄袭或描述失实的内容,请联系我们jiasou666@gmail.com 处理,核实后本网站将在24小时内删除侵权内容。