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。

resource queue的创建语法

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

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 QUEUEpostgres=# create resource queue max with (active_statements=1, priority=max);CREATE QUEUEpostgres=# create role max login encrypted password ‘123‘ resource queue max;CREATE ROLEpostgres=# 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. */Datumgp_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。

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