openGauss 3.1.0 版本gs_stack功能解密
不管是测试还是研发,工作中总有遇到各种各样的问题。比如,你有没有遇到过在数据库中执行某个SQL,却一直不返回结果,这时候的你是不是非常想看一下代码执行到了哪个函数?或者是数据库不响应连接,需要查看数据库当前线程的执行情况呢?而在实际生产中,获取生产系统进程堆栈比较麻烦,需要在服务端后台执行gstack命令。本期为大家介绍的openGauss 3.1.0版本中内置gs_stack工具,则可以通过函数调用的方式输出指定线程的堆栈,用于解决现网环境缺少gs_stack工具无法获取调用栈的问题。
内置gs_stack工具介绍
在openGauss的很多客户场景中,会出现gdb、gstack等工具无法使用或当系统出现hang、慢等问题时,无法通过调用栈进行进一步的定位;还有一种情况是登录客户数据库的流程非常繁杂,需要经过层层审批,这时通过gsql等工具连接数据库就相对容易一些。针对以上痛点,通过复用openGauss未使用操作系统信号,并在信号处理函数中获取调用栈的方式开发了调用栈工具,以获得服务端openGauss的调用栈。
获取调用栈主要包含两种方式,一种是通过执行SQL语句获取,另一种是通过gs_ctl工具执行命令获取。
在客户端工具执行gs_stack([tid])函数
使用具有monadmin或者sysadmin用户权限的用户,通过gsql或者其他工具连接数据库;
执行命令:
openGuass=# select * from gs_stack();
返回当前openGauss所有线程的调用栈:
tid | lwtid | stack
---------------+------ +------------------------------------------------------------------
14026731434848 | 2626 | _poll + 0x2d +
| | WaitLatch0rSocket(Latch volatile*,int,int,long) + 0x29f +
| | WaitLatch(Latch voatile*,int,long) + 0x2e +
| | start_thread +oxc5 +
| | clone + OXC5 +
140116075071232| 23864 |__poll + 0x2d + | | poll + 0x81 +
| | WaitLatchOrSocket(Latch volatile*, int, int, long) + 0x6af +
| | WaitLatch(Latch volatile*, int, long) + 0x2e +
| | ckpt_pagewriter_sub_thread_loop() + 0x284 +
| | ckpt_pagewriter_main() + 0x92e +
| | int GaussDbAuxiliaryThreadMain<(knl_thread_role)46>(knl_thread_arg*) + 0x482 +
| | int GaussDbThreadMain<(knl_thread_role)46>(knl_thread_arg*) + 0x854 +
| | InternalThreadFunc(void*) + 0x5c +
| | ThreadStarterFunc(void*) + 0xa4 +
| | start_thread + 0xc5 +
| | clone + 0x6d +
只需要查看某一个线程的调用栈时,执行命令:
openGuass=# select gs_stack(xxx);
说明:
xxx为某个线程的thread_id,能够返回thread_id为xxx的线程的调用栈:
gs_stack
------------------------------------------------------------------------------------------
pthread_sigmask + 0x2a +
gs_signal_recover_mask(__sigset_t) + 0x17 +
gs_signal_send(unsigned long, int, int) + 0x2f9 +
signal_child(unsigned long, int, int) + 0x36 +
get_stack_according_to_tid(unsigned long, StringInfoData*) + 0x191 +
gs_stack(FunctionCallInfoData*) + 0xcb +
unsigned long ExecMakeFunctionResult<false, false, true>(FuncExprState*, ExprContext*, bool*, ExprDoneCond*) + 0x554 +
ExecEvalFunc(FuncExprState*, ExprContext*, bool*, ExprDoneCond*) + 0x147 +
ExecTargetList(List*, ExprContext*, unsigned long*, bool*, ExprDoneCond*, ExprDoneCond*) + 0x15d +
ExecProject(ProjectionInfo*, ExprDoneCond*) + 0x40f +
ExecResult(ResultState*) + 0x1da +
ExecResultWrap(PlanState*) + 0x18 +
ExecProcNode(PlanState*) + 0xde +
ExecutePlan(EState*, PlanState*, CmdType, bool, long, ScanDirection, _DestReceiver*) + 0x1a6 +
standard_ExecutorRun(QueryDesc*, ScanDirection, long) + 0x3d9 +
explain_ExecutorRun(QueryDesc*, ScanDirection, long) + 0x109 +
ExecutorRun(QueryDesc*, ScanDirection, long) + 0x1ad +
PortalRunSelect(PortalData*, bool, long, _DestReceiver*) + 0x294 +
PortalRun(PortalData*, long, bool, _DestReceiver*, _DestReceiver*, char*) + 0x62e +
exec_simple_query(char const*, MessageType, StringInfoData*) + 0x12b0 +
PostgresMain(int, char**, char const*, char const*) + 0x2e10 +
BackendRun(Port*) + 0x327 +
int GaussDbThreadMain<(knl_thread_role)1>(knl_thread_arg*) + 0x5a8 +
InternalThreadFunc(void*) + 0x2d +
ThreadStarterFunc(void*) + 0xa4 +
start_thread + 0xc5 +
clone + 0x6d +
openGauss=# select gs_stack(140115727259392);
gs_stack
--------------------------------------------------------------------------------------------
__select + 0x33 +
pg_usleep(long) + 0xa1 +
pg_sleep(FunctionCallInfoData*) + 0xeb +
unsigned long ExecMakeFunctionResultNoSets<false, false>(FuncExprState*, ExprContext*, bool*, ExprDoneCond*) + 0x206f +
ExecEvalFunc(FuncExprState*, ExprContext*, bool*, ExprDoneCond*) + 0x622 +
ExecTargetList(List*, ExprContext*, unsigned long*, bool*, ExprDoneCond*, ExprDoneCond*) + 0x45d +
ExecProject(ProjectionInfo*, ExprDoneCond*) + 0xc2d +
ExecResult(ResultState*) + 0x79b +
ExecResultWrap(PlanState*) + 0x18 +
ExecProcNode(PlanState*) + 0x2db +
ExecutePlan(EState*, PlanState*, CmdType, bool, long, ScanDirection, _DestReceiver*) + 0x765 +
standard_ExecutorRun(QueryDesc*, ScanDirection, long) + 0xbb5 +
explain_ExecutorRun(QueryDesc*, ScanDirection, long) + 0x1f7 +
ExecutorRun(QueryDesc*, ScanDirection, long) + 0x947 +
PortalRunSelect(PortalData*, bool, long, _DestReceiver*) + 0x7d2 +
PortalRun(PortalData*, long, bool, _DestReceiver*, _DestReceiver*, char*) + 0xe11 +
exec_simple_query(char const*, MessageType, StringInfoData*) + 0x3929 +
PostgresMain(int, char**, char const*, char const*) + 0x61f8 +
BackendRun(Port*) + 0x64d +
int GaussDbThreadMain<(knl_thread_role)1>(knl_thread_arg*) + 0x9c7 +
InternalThreadFunc(void*) + 0x5c +
ThreadStarterFunc(void*) + 0xa4 +
start_thread + 0xc5 +
clone + 0x6d
在服务器端使用gs_ctl stack –D data_dir命令
当线程池满,无法通过gsql连接数据库的时候,可以使用gs_ctl工具执行命令获取线程调用栈:
使用集群用户登录服务器,执行命令gs_ctl stack –D data_dir,data_dir是指定gaussdb的数据目录的绝对路径:
gs_ctl stack –D /path/to/install/data/
可以取gaussdb所有线程的调用栈。
[user@euler omm]$ gs_ctl stack -D /path/to/install/data/opengauss
[2022-11-03 20:17:59.288][19256][][gs_ctl]: gs_stack start:
Thread 0 tid<140120252633600> lwtid<23675>
__poll + 0x2d
poll + 0x81
CommWaitPollParam::caller(int (*)(pollfd*, unsigned long, int), unsigned long) + 0xb1
int comm_socket_call<CommWaitPollParam, int (*)(pollfd*, unsigned long, int)>(CommWaitPollParam*, int (*)(pollfd*, unsigned long, int)) + 0x28
comm_poll(pollfd*, unsigned long, int) + 0x388
ServerLoop() + 0xb77
PostmasterMain(int, char**) + 0x612e
main + 0xaeb
__libc_start_main + 0xf5
0x55feac9a9907
Thread 1 tid<140116236076800> lwtid<23848>
__poll + 0x2d
poll + 0x81
WaitLatchOrSocket(Latch volatile*, int, int, long) + 0x6af
SysLoggerMain(int) + 0x17c9
int GaussDbThreadMain<(knl_thread_role)17>(knl_thread_arg*) + 0x860
InternalThreadFunc(void*) + 0x5c
ThreadStarterFunc(void*) + 0xa4
start_thread + 0xc5
clone + 0x6d
只需要查看某一个线程的调用栈时,执行命令:
gs_ctl stack –D data_dir –I xx
说明
data_dir是指定gaussdb的数据目录的绝对路径,xxx指的是线程的lwpid(taskid),可以通过top –Hp的方式获取线程的lwpid, 也可以通过cat /proc/yyyy/task获取线程的lwpid 。yyyy指的是进程id,可以通过ps –ux | grep gaussdb获取。
[uesr@euler omm]$ gs_ctl stack -D /path/to/install/data -I 23860
[2022-11-03 20:22:01.327][40608][][gs_ctl]: gs_stack start:
tid<140116142843648> lwtid<23860>
__poll + 0x2d
poll + 0x81
WaitLatchOrSocket(Latch volatile*, int, int, long) + 0x6af
WaitLatch(Latch volatile*, int, long) + 0x2e
ckpt_pagewriter_sub_thread_loop() + 0x284
ckpt_pagewriter_main() + 0x92e
int GaussDbAuxiliaryThreadMain<(knl_thread_role)46>(knl_thread_arg*) + 0x482
int GaussDbThreadMain<(knl_thread_role)46>(knl_thread_arg*) + 0x854
InternalThreadFunc(void*) + 0x5c
ThreadStarterFunc(void*) + 0xa4
start_thread + 0xc5
clone + 0x6d
总结
通过以上我们介绍的openGauss的gs_stack功能,我们可以很方便地定位某个openGauss线程正在做的事情,并可以根据这些函数调用情况判断当前openGauss任务是否出现了问题,以及发现性能瓶颈。后续,我们将会进一步在这个功能上进行演进,不断增强openGauss的核心竞争力。
文章转载自公众号: openGauss