TAG 11

作者

digoal

日期

2016-07-18

标签

Greenplum , 资源隔离 , 源码浅析

---

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 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。

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