Greenplum 资源隔离的原理与源码分析-阿里云开发者社区

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Greenplum 资源隔离的原理与源码分析

简介: 背景 Greenplum是一个MPP的数据仓库系统,最大的优点是水平扩展,并且一个QUERY就能将硬件资源的能力发挥到极致。 但这也是被一些用户诟病的一点,因为一个的QUERY就可能占光所有的硬件资源,所以并发一多的话,query相互之间的资源争抢就比较严重。 Greenplum资源隔

背景

Greenplum是一个MPP的数据仓库系统,最大的优点是水平扩展,并且一个QUERY就能将硬件资源的能力发挥到极致。

但这也是被一些用户诟病的一点,因为一个的QUERY就可能占光所有的硬件资源,所以并发一多的话,query相互之间的资源争抢就比较严重。

Greenplum资源隔离的手段

Greenplum为了降低并发query之间的资源争抢,设计了一套基于resource queue的资源管理方法。

每个resource queue定义了资源的使用或限制模式,根据用户的用途将用户指派给resource queue,这样就起到了资源管理的目的。

例如将分析师、跑报表的、ETL分为三用户。根据这三类用户的预期资源使用情况,以及任务的优先级,规划三类资源管理的队列。分别将三类用户和三类resource queue绑定,起到资源控制的作用。
screenshot

resource queue的创建语法

screenshot

支持的资源隔离类别

  • active_statements, 该queue同时可以运行的query数量。
  • max_cost,指资源组内所有正在运行的query的评估成本的最大值。
  • cost_overcommit,当系统空闲时,是否允许该queue的query总cost超出设定的max_cost。
  • min_cost 指低于该值的QUERY不计入该queue 的cost成本,也不排队,而是直接执行。
  • priority , 用于平衡各个QUEUE之间的CPU争抢使用,分为5个等级,每个等级设定了响应的weight,间隔一定的时间判断使用的资源是否达到了weight,然后对该queue 的query使用pg_usleep进行抑制。
  • mem_limit , 为队列中单个segment query(s)允许的最大statement(s)运行内存。

创建resource queue时必须设置active_statements与max_cost之一。

只有超级用户能创建和修改resource queue。

绑定角色与resource queue
screenshot

resource queue用法举例

创建两个资源队列,指派给两个用户(一个资源队列可以指派给多个用户)。

postgres=# create resource queue min with (active_statements=3, priority=min);
CREATE QUEUE
postgres=# create resource queue max with (active_statements=1, priority=max);
CREATE QUEUE
postgres=# create role max login encrypted password '123' resource queue max;
CREATE ROLE
postgres=# create role min login encrypted password '123' resource queue min;
CREATE ROLE

Greenplum资源隔离的相关代码

src/include/catalog/pg_resqueue.h

#define PG_RESRCTYPE_ACTIVE_STATEMENTS  1       /* rsqcountlimit:                       count  */
#define PG_RESRCTYPE_MAX_COST                   2       /* rsqcostlimit:                max_cost */
#define PG_RESRCTYPE_MIN_COST                   3       /* rsqignorecostlimit:          min_cost */
#define PG_RESRCTYPE_COST_OVERCOMMIT    4       /* rsqovercommit:                       cost_overcommit*/
                        /* start of "pg_resourcetype" entries... */
#define PG_RESRCTYPE_PRIORITY                   5       /* backoff.c:                   priority queue */
#define PG_RESRCTYPE_MEMORY_LIMIT               6       /* memquota.c:                  memory quota */

接下来我挑选了CPU的资源调度进行源码的分析,其他的几个本文就不分析了。

CPU的资源隔离

src/backend/postmaster/backoff.c
五个CPU优先级级别,以及对应的weight(可通过gp_adjust_priority函数调整当前query的weight)。

typedef struct PriorityMapping
{
        const char *priorityVal;
        int weight;
} PriorityMapping;

const struct PriorityMapping priority_map[] = {
                {"MAX", 1000000},
                {"HIGH", 1000},
                {"MEDIUM", 500},
                {"LOW", 200},
                {"MIN", 100},
                /* End of list marker */
                {NULL, 0}
};

单个进程的资源使用统计信息数据结构

/**
 * This is information that only the current backend ever needs to see.
 */
typedef struct BackoffBackendLocalEntry
{
        int                                     processId;              /* Process Id of backend */
        struct rusage           startUsage;             /* Usage when current statement began. To account for caching of backends. */
        struct rusage           lastUsage;              /* Usage statistics when backend process performed local backoff action */
        double                          lastSleepTime;  /* Last sleep time when local backing-off action was performed */
        int                             counter;                /* Local counter is used as an approx measure of time */
        bool                            inTick;                 /* Is backend currently performing tick? - to prevent nested calls */
        bool                            groupingTimeExpired;    /* Should backend try to find better leader? */
} BackoffBackendLocalEntry;

单个segment或master内所有进程共享的资源使用统计信息数据结构

/**
 * There is a backend entry for every backend with a valid backendid on the master and segments.
 */
typedef struct BackoffBackendSharedEntry
{
        struct  StatementId     statementId;            /* A statement Id. Can be invalid. */
        int                                     groupLeaderIndex;       /* Who is my leader? */
        int                                     groupSize;                      /* How many in my group ? */
        int                                     numFollowers;           /* How many followers do I have? */

        /* These fields are written by backend and read by sweeper process */
        struct timeval          lastCheckTime;          /* Last time the backend process performed local back-off action.
                                                                                                Used to determine inactive backends. */

        /* These fields are written to by sweeper and read by backend */
        bool                            noBackoff;                      /* If set, then no backoff to be performed by this backend */
        double                          targetUsage;            /* Current target CPU usage as calculated by sweeper */
        bool                            earlyBackoffExit;       /* Sweeper asking backend to stop backing off */

        /* These fields are written to and read by sweeper */
        bool                            isActive;                       /* Sweeper marking backend as active based on lastCheckTime */
        int                                     numFollowersActive;     /* If backend is a leader, this represents number of followers that are active */

        /* These fields are wrtten by backend during init and by manual adjustment */
        int                                     weight;                         /* Weight of this statement */
} BackoffBackendSharedEntry;


/* In ms */
#define MIN_SLEEP_THRESHOLD  5000

/* In ms */
#define DEFAULT_SLEEP_TIME 100.0

通过getrusage()系统调用获得进程的资源使用情况

        /* Provide tracing information */
        PG_TRACE1(backoff__localcheck, MyBackendId);

        if (gettimeofday(&currentTime, NULL) < 0)
        {
                elog(ERROR, "Unable to execute gettimeofday(). Please disable query prioritization.");
        }

        if (getrusage(RUSAGE_SELF, &currentUsage) < 0)
        {
                elog(ERROR, "Unable to execute getrusage(). Please disable query prioritization.");
        }

资源使用换算

        if (!se->noBackoff)
        {

                /* How much did the cpu work on behalf of this process - incl user and sys time */
                thisProcessTime = TIMEVAL_DIFF_USEC(currentUsage.ru_utime, le->lastUsage.ru_utime)
                                                                                + TIMEVAL_DIFF_USEC(currentUsage.ru_stime, le->lastUsage.ru_stime);

                /* Absolute cpu time since the last check. This accounts for multiple procs per segment */
                totalTime = TIMEVAL_DIFF_USEC(currentTime, se->lastCheckTime);

                cpuRatio = thisProcessTime / totalTime;

                cpuRatio = Min(cpuRatio, 1.0);

                changeFactor = cpuRatio / se->targetUsage;      // 和priority的weight有关,   
        // 和参数gp_resqueue_priority_cpucores_per_segment有关, double CPUAvailable = numProcsPerSegment(); 有关,   
        // se->targetUsage = (CPUAvailable) * (se->weight) / activeWeight / gl->numFollowersActive;

                le->lastSleepTime *= changeFactor;  // 计算是否需要sleep

                if (le->lastSleepTime < DEFAULT_SLEEP_TIME)
                        le->lastSleepTime = DEFAULT_SLEEP_TIME;

超出MIN_SLEEP_THRESHOLD则进入休眠

                memcpy( &le->lastUsage, &currentUsage, sizeof(currentUsage));
                memcpy( &se->lastCheckTime, &currentTime, sizeof(currentTime));

                if (le->lastSleepTime > MIN_SLEEP_THRESHOLD)  // 计算是否需要sleep
                {
                        /*
                         * Sleeping happens in chunks so that the backend may exit early from its sleep if the sweeper requests it to.
                         */
                        int j =0;
                        long sleepInterval = ((long) gp_resqueue_priority_sweeper_interval) * 1000L;
                        int numIterations = (int) (le->lastSleepTime / sleepInterval);
                        double leftOver = (double) ((long) le->lastSleepTime % sleepInterval);
                        for (j=0;j<numIterations;j++)
                        {
                                /* Sleep a chunk */
                                pg_usleep(sleepInterval);   // 休眠
                                /* Check for early backoff exit */
                                if (se->earlyBackoffExit)
                                {
                                        le->lastSleepTime = DEFAULT_SLEEP_TIME;   /* Minimize sleep time since we may need to recompute from scratch */
                                        break;
                                }
                        }
                        if (j==numIterations)
                                pg_usleep(leftOver);
                }
        }

除了前面的休眠调度,还需要考虑当数据库空闲的时候,应该尽量使用数据库的资源,那么什么情况下不进入休眠呢?

        /**
         * Under certain conditions, we want to avoid backoff. Cases are:
         * 1. A statement just entered or exited
         * 2. A statement's weight changed due to user intervention via gp_adjust_priority()
         * 3. There is no active backend
         * 4. There is exactly one statement
         * 5. Total number valid of backends <= number of procs per segment(gp_resqueue_priority_cpucores_per_segment 参数设置)
         * Case 1 and 2 are approximated by checking if total statement weight changed since last sweeper loop.
         */

如何调整正在执行的query的weight

当正在执行一个query时,如果发现它太占资源,我们可以动态的设置它的weight。

当一个query正在执行时,可以调整它的priority

postgres=# set gp_debug_resqueue_priority=on;
postgres=# set client_min_messages ='debug';

查询当前的resource queue priority  
postgres=# select * from gp_toolkit.gp_resq_priority_statement;
 rqpdatname | rqpusename | rqpsession | rqpcommand | rqppriority | rqpweight |                        rqpquery                        
------------+------------+------------+------------+-------------+-----------+--------------------------------------------------------
 postgres   | digoal     |         21 |          1 | MAX         |   1000000 | select pg_sleep(1000000) from gp_dist_random('gp_id');
 postgres   | digoal     |         22 |          1 | MAX         |   1000000 | select pg_sleep(1000000) from gp_dist_random('gp_id');
 postgres   | digoal     |         23 |          1 | MAX         |   1000000 | select pg_sleep(1000000) from gp_dist_random('gp_id');
 postgres   | digoal     |         24 |          1 | MAX         |   1000000 | select pg_sleep(1000000) from gp_dist_random('gp_id');
 postgres   | digoal     |         25 |          1 | MAX         |   1000000 | select pg_sleep(1000000) from gp_dist_random('gp_id');
 postgres   | digoal     |         26 |         65 | MAX         |   1000000 | select * from gp_toolkit.gp_resq_priority_statement;
(6 rows)

设置,可以直接设置priority的别名(MIN, MAX, LOW, HIGH, MEDIAM),或者使用数字设置weight。  
postgres=# select gp_adjust_priority(21,1,'MIN');
LOG:  changing weight of (21:1) from 1000000 to 100
 gp_adjust_priority 
--------------------
                  1
(1 row)
postgres=# select * from gp_toolkit.gp_resq_priority_statement;
 rqpdatname | rqpusename | rqpsession | rqpcommand | rqppriority | rqpweight |                        rqpquery                        
------------+------------+------------+------------+-------------+-----------+--------------------------------------------------------
 postgres   | digoal     |         21 |          1 | MIN         |       100 | select pg_sleep(1000000) from gp_dist_random('gp_id');

600是一个非标准的priority,所以显示NON-STANDARD  
postgres=# select gp_adjust_priority(21,1,600);
postgres=# select * from gp_toolkit.gp_resq_priority_statement;
 rqpdatname | rqpusename | rqpsession | rqpcommand | rqppriority  | rqpweight |                        rqpquery                        
------------+------------+------------+------------+--------------+-----------+--------------------------------------------------------
 postgres   | digoal     |         21 |          1 | NON-STANDARD |       600 | select pg_sleep(1000000) from gp_dist_random('gp_id');

代码如下

/**
 * An interface to re-weigh an existing session on the master and all backends.
 * Input:
 *      session id - what session is statement on?
 *      command count - what is the command count of statement.
 *      priority value - text, what should be the new priority of this statement.
 * Output:
 *      number of backends whose weights were changed by this call.
 */
Datum
gp_adjust_priority_value(PG_FUNCTION_ARGS)
{
        int32 session_id = PG_GETARG_INT32(0);
        int32 command_count = PG_GETARG_INT32(1);
        Datum           dVal = PG_GETARG_DATUM(2);
        char *priorityVal = NULL;
        int wt = 0;

        priorityVal = DatumGetCString(DirectFunctionCall1(textout, dVal));

        if (!priorityVal)
        {
                elog(ERROR, "Invalid priority value specified.");
        }

        wt = BackoffPriorityValueToInt(priorityVal);

        Assert(wt > 0);

        pfree(priorityVal);

        return DirectFunctionCall3(gp_adjust_priority_int, Int32GetDatum(session_id),
                                                                Int32GetDatum(command_count), Int32GetDatum(wt));

}

通过cgroup细粒度控制query的资源使用

前面讲的是Greenplum通过自带的resource queue来控制资源使用的情况,但是Greenplum控制的资源种类有限,有没有更细粒度的控制方法呢?

如果要进行更细粒度的控制,可以考虑使用cgroup来隔离各个query的资源使用。

可以做到对cpu, memory, iops, network的细粒度控制。

做法也很简单,
首先要在所有的物理主机创建对应的cgroup,例如为每个资源分配几个等级。

  • cpu: 分若干个等级
  • memory: 分若干个等级
  • iops: 分若干个等级
  • network: 分若干个等级

_

然后获得会话对应的所有节点的backend pid,将backend pid move到对应的cgroup即可。
_1

祝大家玩得开心,欢迎随时来阿里云促膝长谈业务需求 ,恭候光临。

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