SingleStoreDB v7.6

Configure Cluster Monitoring with the Operator

Configure the Exporter Process

The monitoring exporter should already be running in a container in the Master node Pod on the Source cluster.

If Metrics and Source clusters are the same or are located in the same Kubernetes cluster (in different namespaces, for example), no further action is required, and you may skip to the next step.

If Metrics and Source clusters are located in different Kubernetes clusters, the exporter process must be exposed to outside of the cluster as a service (such as a Load Balancer service) and this service must be accessible from all nodes in the Metrics cluster.

For example:

Retrieve the ownerReferences UID.

kubectl get svc svc-k8s-cluster-ddl -o jsonpath='{.metadata.ownerReferences}'

Retrieve the metadata UID.

kubectl get svc svc-k8s-cluster-ddl -o jsonpath='{.metadata.uid}'

Modify the svc-k8s-cluster-exporter.yaml file using the UID values retrieved in the above steps.

apiVersion: v1
kind: Service
metadata:
  annotations:
    custom: annotations
    service.beta.kubernetes.io/aws-load-balancer-connection-idle-timeout: "4000"
  labels:
    app.kubernetes.io/component: master
    app.kubernetes.io/instance: <memsql-cluster-name>
    app.kubernetes.io/name: memsql-cluster
    custom: label
  name: svc-<memsql-cluster-name>-exporter
  namespace: default
  ownerReferences:
  - apiVersion: memsql.com/v1alpha1
    controller: true
    kind: MemsqlCluster
    name:<memsql-cluster-name>
    uid: <ownerReferences-UID>         # Update with ownerReferences UID
  resourceVersion: "615"
  uid: <metadata-UID>                  # Update with metadata UID
spec:
  externalTrafficPolicy: Cluster
  ipFamilies:
  - IPv4
  ipFamilyPolicy: SingleStack
  ports:
  - name: prometheus
    port: 9104
    protocol: TCP
  selector:
    app.kubernetes.io/instance: <memsql-cluster-name>
    app.kubernetes.io/name: memsql-cluster
    statefulset.kubernetes.io/pod-name: node-<memsql-cluster-name>-master-0
  sessionAffinity: None
  type: LoadBalancer
status:
  loadBalancer: {}

Create the exporter service.

kubectl create -f svc-k8s-cluster-exporter.yaml

Configure the Metrics Database

Determine the Hostname of the Exporter

From the previous step, if the Metrics and Source clusters are the same or are located in the same Kubernetes cluster, then <name of the master pod>.svc-<cluster name>.<namespace containing the Source cluster master pod>.svc.cluster.local can be used as the exporter hostname in this section.

However, if the Metrics and Source clusters are located in different Kubernetes clusters, then a hostname/IP address of the created service that can be reached by each node of the Metrics cluster can be used as the exporter hostname in this section.

Configure the Metrics Database with the Tools Pod

Note

This is the recommended method, and the minimum required version (tag) of the Tools image is alma-v1.11.6-1.15.0-9aeaf4773aabf53549df18a6bd9f6399edb30b08.

Create and Apply the Tools RBAC

Either use an existing account with sufficient permissions or create a service account that can be used for running the Tools Pod.

Save the following to a tools-rbac.yaml file.

apiVersion: v1
kind: ServiceAccount
metadata:
  name: tools
---
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  namespace: default
  name: tools-role
rules:
  - apiGroups:
      - ""
    resources:
      - pods
      - services
      - namespaces
    verbs:
      - get
      - list
  - apiGroups: [ "" ]
    resources: [ "pods/exec" ]
    verbs: [ "create" ]
  - apiGroups:
      - apps
    resources:
      - statefulsets
    verbs:
      - get
      - list
  - apiGroups:
      - memsql.com
    resources:
      - '*'
    verbs:
      - get
      - list
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: tools
  namespace: default
subjects:
  - kind: ServiceAccount
    name: tools
roleRef:
  kind: Role
  name: tools-role
  apiGroup: rbac.authorization.k8s.io

Apply the tools-rbac.yaml file to the cluster. This creates a tools service account with the required permissions.
```
kubectl apply -f tools-rbac.yaml
```

Create and Apply the Start Monitoring Job

The following YAML creates a job that sets up the metrics database and the associated pipelines.

With Internet Access

Modify the start-monitoring-job.yaml. so that it resembles the following. Note that:

<database-user> must be replaced with the desire database user, such as the admin user
<database-user-password> must be replaced with this database user’s password
<exporter-hostname> must be replaced with the exporter hostname from the Determine the Hostname of the Exporter step
<other-options…> must be removed or replaced with those options available in sdb-admin start-monitoring-kube

apiVersion: batch/v1
kind: Job
metadata:
  name: toolbox-start-monitoring
spec:
  template:
    spec:
      serviceAccountName: tools
      containers:
      - name: toolbox-start-monitoring
        image: singlestore/tools:alma-v1.11.6-1.15.1-bba39e8c3d64bb1f65cf123f175dc43c40e22e68
        imagePullPolicy: IfNotPresent
        command: ["sdb-admin",
                  "start-monitoring-kube",
                  "--user=<database-user>",
                  "--password=<database-user-password>",
                  "--exporter-host=<exporter-hostname>",
                  "--yes"
		<other options…>
                  ]
      restartPolicy: Never
  backoffLimit: 2

Run the following command to apply the changes in the start-monitoring-job.yaml file.
```
kubectl apply -f start-monitoring-job.yaml
```

Without Internet Access

The following steps are only required for those deployment environments that cannot access the internet and therefore require the use of a local registry.

Run the following command to pull the SingleStore Tools image from Docker Hub.

docker pull singlestore/tools:alma-v1.11.6-1.15.1-bba39e8c3d64bb1f65cf123f175dc43c40e22e68

Push this image to a container image registry that is accessible by your deployment.

docker push <internal-registry-name>/singlestore/tools:alma-v1.11.6-1.15.1-bba39e8c3d64bb1f65cf123f175dc43c40e22e68

Modify the start-monitoring-job.yaml file so that it resembles the following. Note that:

<database-user> must be replaced with the desire database user, such as the admin user
<database-user-password> must be replaced with this database user’s password
<exporter-hostname> must be replaced with the exporter hostname from the Determine the Hostname of the Exporter step
<other-options…> must be removed or replaced with those options available in sdb-admin start-monitoring-kube

apiVersion: batch/v1
kind: Job
metadata:
  name: toolbox-start-monitoring
spec:
  template:
    spec:
      serviceAccountName: tools
      containers:
      - name: toolbox-start-monitoring
        image: <internal-registry-name>singlestore/tools:alma-v1.11.6-1.15.1-bba39e8c3d64bb1f65cf123f175dc43c40e22e68        # Update this line
        imagePullPolicy: IfNotPresent
        command: ["sdb-admin",
                  "start-monitoring-kube",
                  "--user=<database-user>",
                  "--password=<database-user-password>",
                  "--exporter-host=<exporter-hostname>",
                  "--yes"
		<other-options…>
                  ]
      restartPolicy: Never
  backoffLimit: 2

Run the following command to apply the changes in the start-monitoring-job.yaml file.
```
kubectl apply -f start-monitoring-job.yaml
```

Confirm the Start Monitoring Job is Running

Run the following command to confirm that the job has finished successfully. The output displayed will be Completions 1/1 for toolbox-start-monitoring.

kubectl get jobs
****
NAME                       COMPLETIONS   DURATION   AGE
toolbox-start-monitoring   1/1           13s        21s

You may terminate this job by running the following command.

kubectl delete -f start-monitoring-job.yaml

As of Kubernetes 1.23, ttlSecondsAfterFinished: <seconds> may be added to the job spec to automatically remove the finished job within the specified number of seconds.

Configure the Metrics Database without the Tools Pod

Note

The following steps are only required if the metrics database cannot be configured via the Tools Pod.

The metrics database can either reside in the Source cluster, or in a dedicated Metrics cluster.

Note that the user that creates the metrics database may differ from the one that started the exporter. This user must be able to create tables, databases, and pipelines. At a minimum, the following permissions are required:

`metrics` Database DDL

You may run the following SQL scripts to configure the database.

Please note the following:

The database that is created to store monitoring data is named metrics by default. You must edit these SQL statements manually to change the database name.
The database user is root by default. When creating the metrics database with a database user other than root, the SUPER privilege must be granted to this user. For example, for a dbmon user:
GRANT SUPER ON *.* TO 'dbmon'@'%';
These commands must be run on the Master Aggregator of the Metrics cluster.

Create the metrics database and associated tables by copying, pasting, and executing each set of SQL statements below. This can be done via the SQL Editor in Studio, or your favored SQL client.

You may also download the latest metrics database DDL SQL file from SingleStore.

View the `metrics` Database DDL

create database if not exists metrics;

CREATE TABLE IF NOT EXISTS metrics.config (
    `hostport`      TINYBLOB NOT NULL,
    `retention_period_minutes` INT NOT NULL,
    `purge_frequency_minutes` INT NOT NULL,
    `purge_limit` INT NOT NULL,
    PRIMARY KEY(`hostport`)
);

CREATE TABLE IF NOT EXISTS metrics.`metrics` (
    `labels`                                           JSON,
    `name`                                             TINYBLOB NOT NULL,
    `memsql_tags`                                      JSON COLLATE utf8_bin,
    `cluster` AS `memsql_tags`::$cluster               PERSISTED TINYBLOB,
    `host` AS `labels`::$host                          PERSISTED TINYBLOB,
    `port` as `labels`::$port                          PERSISTED SMALLINT(6),
    `role` as `labels`::$role                          PERSISTED TINYBLOB,
    `extractor` as substring_index(`name`, '_', 1)     PERSISTED TINYBLOB,
    `subsystem` as substring_index(substring_index(`name`, '_', 2), '_', -1) PERSISTED TINYBLOB,
    `job` AS `memsql_tags`::$push_job                  PERSISTED TINYBLOB,
    `value`                                            DOUBLE NOT NULL,
    `intval` AS cast(floor(`value`) AS signed integer) PERSISTED BIGINT(20),
    `time_sec`                                         BIGINT(20) NOT NULL,
    KEY `name` (`cluster`,`extractor`,`subsystem`,`host`,`role`,`name`,`time_sec`) USING CLUSTERED COLUMNSTORE,
    SHARD KEY()
);

CREATE TABLE IF NOT EXISTS metrics.act_samples (
    `cluster` varchar(512) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,
    `memsql_tags` JSON NOT NULL,
    `ts` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    `ACTIVITY_TYPE` varchar(512) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,
    `ACTIVITY_NAME` varchar(512) CHARACTER SET utf8 COLLATE utf8_bin NOT NULL,
    `AGGREGATOR_ACTIVITY_NAME` varchar(512) CHARACTER SET utf8 COLLATE utf8_bin DEFAULT NULL,
    `DATABASE_NAME` varchar(512) CHARACTER SET utf8 COLLATE utf8_bin DEFAULT NULL,
    `NODE_ID` smallint(6) DEFAULT NULL,
    `PARTITION_ID` smallint(6) DEFAULT NULL,
    `CPU_TIME_MS` bigint(4) DEFAULT NULL,
    `CPU_WAIT_TIME_MS` bigint(4) DEFAULT NULL,
    `ELAPSED_TIME_MS` bigint(4) DEFAULT NULL,
    `LOCK_TIME_MS` bigint(4)  DEFAULT NULL,
    `NETWORK_TIME_MS` bigint(4)  DEFAULT NULL,
    `DISK_TIME_MS` bigint(4) DEFAULT NULL,
    `DISK_B` bigint(4) DEFAULT NULL,
    `DISK_LOGICAL_READ_B` bigint(4) DEFAULT NULL,
    `DISK_LOGICAL_WRITE_B` bigint(4) DEFAULT NULL,
    `DISK_PHYSICAL_READ_B` bigint(4) DEFAULT NULL,
    `DISK_PHYSICAL_WRITE_B` bigint(4) DEFAULT NULL,
    `LOCK_ROW_TIME_MS` bigint(4) DEFAULT NULL,
    `LOG_FLUSH_TIME_MS` bigint(4) DEFAULT NULL,
    `LOG_BUFFER_TIME_MS` bigint(4) DEFAULT NULL,
    `LOG_BUFFER_WRITE_B` bigint(4) DEFAULT NULL,
    `NETWORK_B` bigint(4) DEFAULT NULL,
    `NETWORK_LOGICAL_RECV_B` bigint(4) DEFAULT NULL,
    `NETWORK_LOGICAL_SEND_B` bigint(4) DEFAULT NULL,
    `MEMORY_BS` bigint(4) DEFAULT NULL,
    `MEMORY_MAJOR_FAULTS` bigint(4) DEFAULT NULL,
    `RUN_COUNT` bigint(4)  NULL DEFAULT '0',
    `SUCCESS_COUNT` bigint(4)  NULL DEFAULT '0',
    `FAILURE_COUNT` bigint(4)  NULL DEFAULT '0',
    KEY (`cluster`, `ACTIVITY_TYPE`,`ACTIVITY_NAME`,`AGGREGATOR_ACTIVITY_NAME`,`DATABASE_NAME`,`NODE_ID`,`PARTITION_ID`,ts) USING CLUSTERED COLUMNSTORE,
    SHARD KEY()
);

create table IF NOT EXISTS metrics.mv_queries
(
    `cluster` varchar(512) NOT NULL,
    `memsql_tags` JSON NOT NULL,
    `ts` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
    `ACTIVITY_NAME` varchar(512),
    `QUERY_TEXT` longtext,
    `PLAN_WARNINGS` varchar(8192),
    KEY (`cluster`, `ACTIVITY_NAME`) USING CLUSTERED COLUMNSTORE,
    SHARD KEY()
);

create table IF NOT EXISTS metrics.cluster_info
(
    `cluster` varchar(512) NOT NULL,
    `memsql_tags` JSON NOT NULL,
    `ts` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    `status` JSON NOT NULL,
    KEY (cluster, ts) USING CLUSTERED COLUMNSTORE,
    SHARD KEY()
);

create table IF NOT EXISTS metrics.db_status
(
    `memsql_tags` JSON NOT NULL,
    `keys` JSON NOT NULL,
    `values` JSON NOT NULL,
    `ts` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
    `cluster` AS `memsql_tags`::$cluster          PERSISTED TINYBLOB,
    database_name AS `keys`::$database_name       PERSISTED TINYBLOB,
    `role` as `keys`::$role                       PERSISTED tinyblob,
    num_partitions as `values`::$num_partitions   PERSISTED SMALLINT(6),
    `online` as `values`::$online                 PERSISTED SMALLINT(6),
    `offline` as `values`::$offline               PERSISTED SMALLINT(6),
    replicating as `values`::$replicating         PERSISTED SMALLINT(6),
    recovering as `values`::$recovering           PERSISTED SMALLINT(6),
    pending as `values`::$pending                 PERSISTED SMALLINT(6),
    transition as `values`::$transition           PERSISTED SMALLINT(6),
    unrecoverable as `values`::$unrecoverable     PERSISTED SMALLINT(6),
    ref_db_state as `values`::$ref_db_state       PERSISTED TINYBLOB,
    summary as `values`::$summary                 PERSISTED TINYBLOB,
    KEY (cluster, database_name, ts) USING CLUSTERED COLUMNSTORE,
    SHARD KEY()
);

create table if not exists metrics.mv_events
(
    `memsql_tags` JSON NOT NULL,
    `keys` JSON NOT NULL,
    `values` JSON NOT NULL,
    ts TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
    event_ts TIMESTAMP,
    `cluster` AS `memsql_tags`::$cluster          PERSISTED TINYBLOB,
    `event_type` AS `keys`::$event_type           PERSISTED TINYBLOB,
    `origin_node_id` AS `keys`::$origin_node_id   PERSISTED SMALLINT,
    `ip_addr` AS `values`::$ip_addr               PERSISTED TINYBLOB,
    `port` AS `values`::$port                     PERSISTED SMALLINT,
    `type` AS `values`::$type                     PERSISTED TINYBLOB,
    `severity` as `keys`::$severity               PERSISTED TINYBLOB,
    `details` as `values`::$details               PERSISTED TINYBLOB,
    KEY (cluster, origin_node_id, event_ts) USING CLUSTERED COLUMNSTORE,
    SHARD KEY()
);

create table if not exists metrics.mv_nodes
(
    `memsql_tags` JSON NOT NULL,
    `keys` JSON NOT NULL,
    `values` JSON NOT NULL,
    `ts` TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
    `cluster`                AS `memsql_tags`::$cluster            PERSISTED TINYBLOB,
    `node_id`                AS `keys`::$node_id                   PERSISTED SMALLINT,
    `ip_addr`                AS `keys`::$ip_addr                   PERSISTED TINYBLOB,
    `port`                   AS `keys`::$port                      PERSISTED SMALLINT,
    `role`                   AS `keys`::$role                      PERSISTED TINYBLOB,
    `external_host`          AS `keys`::$external_host             PERSISTED TINYBLOB,
    `external_port`          AS `keys`::$external_port             PERSISTED SMALLINT,
    `state`                  AS `values`::$state                   PERSISTED TINYBLOB,
    `availability_group`     AS `values`::$availability_group      PERSISTED SMALLINT,
    `num_cpus`               AS `values`::$num_cpus                PERSISTED BIGINT,
    `max_memory_mb`          AS `values`::$max_memory_mb           PERSISTED BIGINT,
    `max_table_memory_mb`    AS `values`::$max_table_memory_mb     PERSISTED BIGINT,
    `memory_used_mb`         AS `values`::$memory_used_mb          PERSISTED BIGINT,
    `table_memory_used_mb`   AS `values`::$table_memory_used_mb    PERSISTED BIGINT,
    `total_data_disk_mb`     AS `values`::$total_data_disk_mb      PERSISTED BIGINT,
    `available_data_disk_mb` AS `values`::$available_data_disk_mb  PERSISTED BIGINT,
    `uptime`                 AS `values`::$uptime                  PERSISTED BIGINT,
    `version`                AS `values`::$version                 PERSISTED TINYBLOB,
    KEY(`cluster`, `node_id`, `ts`) USING CLUSTERED COLUMNSTORE,
    SHARD KEY()
);

create table if not exists metrics.purge_log
(
    `ts`           TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
    `hostport`         TINYBLOB NOT NULL,
    `rows_deleted` BIGINT NOT NULL,
    `status`       TINYBLOB NOT NULL,
    KEY(`ts`, `hostport`),
    SHARD KEY()
);

delimiter //
create or replace procedure metrics.purge_metrics(current_ts TIMESTAMP, current_hostport TINYBLOB,
    retention_period INT) AS
declare rc int = 1;
declare earliest_ts INT = UNIX_TIMESTAMP(TIMESTAMPADD(MINUTE, -retention_period, current_ts));
begin
    delete from metrics where ifnull(`memsql_tags`::$host, "") = current_hostport and time_sec < earliest_ts;
    rc = row_count();
    update purge_log set rows_deleted = rows_deleted + rc where `hostport` = current_hostport and `ts` = current_ts;
end //
delimiter ;

delimiter //
create or replace procedure metrics.purge_blobs(current_ts TIMESTAMP, current_hostport TINYBLOB,
    retention_period INT) AS
declare rc int = 1;
declare earliest_ts TIMESTAMP = TIMESTAMPADD(MINUTE, -retention_period, current_ts);
begin
    delete from act_samples where ifnull(`memsql_tags`::$host, "") = current_hostport and ts < earliest_ts;
    rc = row_count();
    delete from mv_events where ifnull(`memsql_tags`::$host, "") = current_hostport and ts < earliest_ts;
    rc += row_count();
    delete from mv_queries where ifnull(`memsql_tags`::$host, "") = current_hostport and ts < earliest_ts;
    rc += row_count();
    delete from cluster_info where ifnull(`memsql_tags`::$host, "") = current_hostport and ts < earliest_ts;
    rc += row_count();
    delete from db_status where ifnull(`memsql_tags`::$host, "") = current_hostport and ts < earliest_ts;
    rc += row_count();
    delete from mv_nodes where ifnull(`memsql_tags`::$host, "") = current_hostport and ts < earliest_ts;
    rc += row_count();
    update purge_log set rows_deleted = rows_deleted + rc where `hostport` = current_hostport and `ts` = current_ts;
end //
delimiter ;

-- This procedure purges monitoring data that is older than the retention period set in the config table.
-- To prevent overrunning this we use purge_log table in order to track when the last purge
-- was completed. New purge process won't start unless at least some time passed since previous purge,
-- controlled by `purge_frequency_minutes` in the config table.
delimiter //
CREATE or replace PROCEDURE metrics.purge_data(current_hostport TINYBLOB) AS
declare
    need_purge_qry QUERY(need_purge BOOLEAN) =
        select (TIMESTAMPDIFF(
            MINUTE,
            (select ifnull(max(ts), from_unixtime(0)) from purge_log
              where hostport = current_hostport),
            CURRENT_TIMESTAMP()
        )>=(select ifnull(ANY_VALUE(purge_frequency_minutes), 60)
              from config
             where hostport = current_hostport) );
    retention_period_qry QUERY(retention_period INT) =
        select ifnull(ANY_VALUE(retention_period_minutes), 10080)
        from config
        where hostport = current_hostport;
    retention_period INT = SCALAR(retention_period_qry);
    current_ts TIMESTAMP;
begin
    IF SCALAR(need_purge_qry) THEN
        BEGIN
            select current_timestamp() into current_ts;
            insert into purge_log values (current_ts, current_hostport, 0, "RUNNING");
            call purge_metrics(current_ts, current_hostport, retention_period);
            call purge_blobs(current_ts, current_hostport, retention_period);
            update purge_log set status = "FINISHED" where `ts` = current_ts;
            EXCEPTION
                WHEN OTHERS THEN
                    update purge_log set status = "FAILED" where `ts` = current_ts and hostport = current_hostport;
            delete from purge_log where TIMESTAMPDIFF(MINUTE, ts, CURRENT_TIMESTAMP()) > 525600;
        END;
    END IF;
end //
delimiter ;

delimiter //
CREATE or replace PROCEDURE metrics.load_metrics (metrics_pipe query(`labels` JSON, `name` TINYBLOB, `memsql_tags` JSON COLLATE utf8_bin,`value` DOUBLE NOT NULL,`time_sec` BIGINT(20) NOT NULL)) AS
DECLARE hostport TINYBLOB;
BEGIN
    INSERT INTO metrics (
        `labels`,
        `name`,
        `memsql_tags`,
        `value`,
        `time_sec`
    ) SELECT
        `labels`,
        `name`,
        `memsql_tags`,
        `value`,
        `time_sec`
        from metrics_pipe;
    SELECT IFNULL(ANY_VALUE(`memsql_tags`::$host), "") INTO hostport FROM metrics_pipe;
    CALL purge_data(hostport);
END //
delimiter ;


delimiter //
create or replace procedure metrics.load_blobs (blobs_pipe query(type text, `keys` JSON, `vals` JSON, time_sec bigint, `memsql_tags` JSON NULL)) AS
DECLARE hostport TINYBLOB;
begin
    insert into act_samples (
        `cluster`,
        `memsql_tags`,
        `ts`,
        `ACTIVITY_TYPE`,
        `ACTIVITY_NAME`,
        `AGGREGATOR_ACTIVITY_NAME`,
        `NODE_ID`,
        `PARTITION_ID`,
        `DATABASE_NAME`,
        `CPU_TIME_MS`,
        `CPU_WAIT_TIME_MS`,
        `ELAPSED_TIME_MS`,
        `LOCK_TIME_MS` ,
        `NETWORK_TIME_MS` ,
        `DISK_TIME_MS`,
        `DISK_B`,
        `DISK_LOGICAL_READ_B`,
        `DISK_LOGICAL_WRITE_B`,
        `DISK_PHYSICAL_READ_B`,
        `DISK_PHYSICAL_WRITE_B`,
        `LOCK_ROW_TIME_MS`,
        `LOG_FLUSH_TIME_MS`,
        `LOG_BUFFER_TIME_MS`,
        `LOG_BUFFER_WRITE_B`,
        `NETWORK_B`,
        `NETWORK_LOGICAL_RECV_B`,
        `NETWORK_LOGICAL_SEND_B`,
        `MEMORY_BS`,
        `MEMORY_MAJOR_FAULTS`,
        `RUN_COUNT`,
        `SUCCESS_COUNT`,
        `FAILURE_COUNT`
    ) select
    `memsql_tags`::$cluster,
    `memsql_tags`,
    FROM_UNIXTIME(time_sec),
    `keys`::$activity_type,
    `keys`::$activity_name,
    `keys`::$aggregator_activity_name,
    `keys`::node_id,
    `keys`::partition_id,
    `keys`::$db_name,
    `vals`::cpu_time_ms,
    `vals`::cpu_wait_time_ms,
    `vals`::elapsed_time_ms,
    `vals`::lock_time_ms,
    `vals`::network_time_ms,
    `vals`::disk_time_ms,
    `vals`::disk_b,
    `vals`::disk_logical_read_b,
    `vals`::disk_logical_write_b,
    `vals`::disk_physical_read_b,
    `vals`::disk_physical_write_b,
    `vals`::lock_row_time_ms,
    `vals`::log_flush_time_ms,
    `vals`::log_buffer_time_ms,
    `vals`::log_buffer_write_b,
    `vals`::network_b,
    `vals`::network_logical_recv_b,
    `vals`::network_logical_send_b,
    `vals`::memory_bs,
    `vals`::memory_major_faults,
    `vals`::run_count,
    `vals`::success_count,
    `vals`::failure_count
    from blobs_pipe
    where type = 'activity';

    insert into mv_events (
        `memsql_tags`,
        `keys`,
        `values`,
        `ts`,
        `event_ts`
    )
    select
    `memsql_tags`,
    `keys`,
    `vals`,
    FROM_UNIXTIME(time_sec),
    FROM_UNIXTIME(`keys`::$event_time)
    from blobs_pipe b
    left join (SELECT distinct cluster,
        origin_node_id,
        event_ts from mv_events) k
    ON b.`memsql_tags`::$cluster = k.cluster
    and b.`keys`::$origin_node_id = k.origin_node_id
    and b.`keys`::$event_time = k.event_ts
    where type = 'event'
    and k.cluster is null
    and k.origin_node_id is null;

    insert into mv_queries (
        `cluster`,
        `ACTIVITY_NAME`,
        `memsql_tags`,
        `ts`,
        `QUERY_TEXT`,
        `PLAN_WARNINGS`
    )
    select
    `memsql_tags`::$cluster,
    `keys`::$activity_name,
    -- memsql_tags and time_sec are the same for the whole batch
    ANY_VALUE(`memsql_tags`),
    FROM_UNIXTIME(ANY_VALUE(time_sec)),
    ANY_VALUE(`vals`::$query_text),
    ANY_VALUE(`vals`::$plan_warnings)
    from blobs_pipe b
    left join (SELECT distinct cluster, ACTIVITY_NAME from mv_queries) k
    ON b.`memsql_tags`::$cluster = k.cluster and b.`keys`::$activity_name = k.ACTIVITY_NAME
    where type = 'query'
    and k.cluster is null and k.ACTIVITY_NAME is null
    group by 1, 2;

    insert into cluster_info (
        `cluster`,
        `memsql_tags`,
        `ts`,
        `status`
    ) select
    `memsql_tags`::$cluster,
    `memsql_tags`,
    FROM_UNIXTIME(time_sec),
    `vals`
    from blobs_pipe
    where type = 'cluster';

    insert into db_status (
        `memsql_tags`,
        `keys`,
        `values`,
        `ts`
    ) select
    `memsql_tags`, `keys`, `vals`, FROM_UNIXTIME(time_sec)
    from blobs_pipe
    where type = 'db_state';

    insert into mv_nodes (
        `memsql_tags`,
        `keys`,
        `values`,
        `ts`
    ) select
    `memsql_tags`, `keys`, `vals`, FROM_UNIXTIME(time_sec)
    from blobs_pipe
    where type = 'node';

    SELECT IFNULL(ANY_VALUE(`memsql_tags`::$host), "") INTO hostport FROM blobs_pipe;
    CALL purge_data(hostport);
end //
delimiter ;

-- Grafana Stuff

delimiter //
CREATE OR REPLACE FUNCTION metrics.`trim_metric`(input varchar(512) CHARACTER SET utf8 COLLATE utf8_general_ci NULL, prefix varchar(255) CHARACTER SET utf8 COLLATE utf8_general_ci NULL) RETURNS varchar(512) CHARACTER SET utf8 COLLATE utf8_general_ci NULL AS begin
  return
  CASE
  WHEN input is not null and prefix is not null and locate(prefix, input, 1) > 0 THEN
    UPPER(substr(input, locate(prefix, input, 1) + length(prefix), length(input) - length(prefix)))
  ELSE input end;
end //
delimiter ;

delimiter //
CREATE OR REPLACE FUNCTION metrics.`trim_host`(input varchar(512) CHARACTER SET utf8 COLLATE utf8_general_ci NULL, c int default 1) RETURNS varchar(512) CHARACTER SET utf8 COLLATE utf8_general_ci NULL AS begin
 return
 CASE
 WHEN input RLIKE '([[:digit:]]{1,3}\\.){3}[[:digit:]]{1,3}' THEN
  input
 ELSE substring_index(input, '.', c) end;
end //
delimiter ;

-- helper table for integers 1..100
drop table if exists metrics.ints;

create reference table metrics.ints
(
    f int key
);

insert into metrics.ints values
(1), (2), (3), (4), (5), (6), (7), (8), (9), (10),
(11), (12), (13), (14), (15), (16), (17), (18), (19), (20),
(21), (22), (23), (24), (25), (26), (27), (28), (29), (30),
(31), (32), (33), (34), (35), (36), (37), (38), (39), (40),
(41), (42), (43), (44), (45), (46), (47), (48), (49), (50),
(51), (52), (53), (54), (55), (56), (57), (58), (59), (60),
(61), (62), (63), (64), (65), (66), (67), (68), (69), (70),
(71), (72), (73), (74), (75), (76), (77), (78), (79), (80),
(81), (82), (83), (84), (85), (86), (87), (88), (89), (90),
(91), (92), (93), (94), (95), (96), (97), (98), (99), (100);

`metrics` Database DDL Variables

The following variables may be set via the metrics DDL file.

Monitoring database name: Default is metrics.
By default, the metrics.config table is empty.
In the case of multi-cluster monitoring, an existing monitoring configuration can be overridden for a specific Source cluster by manually adding a row to this table and specifying:
- The <exporter-host><exporter-port> of the Source cluster, in hostport form
- A retention_period_minutes value, in minutes
- A purge_frequency_minutes value, in minutes
- A purge_limit value, an integer
retention_period_minutes = 10080 minutes (default), which equals 7 days: Period of time to retain monitoring data for a specific Source cluster.
purge_frequency_minutes = 60 (default), minutes: Time between purges of expired monitoring data for a specific Source cluster.
purge_limit = 10000 (default), integer: Maximum number of entries deleted during a monitoring data purge for a specific Source cluster.
Purge log retention period = 525600 minutes (default), which equals 365 days: Period of time to retain purge log entries.
batch_interval = 15000 (default), milliseconds: Time interval between data collections.
high_cardinality_metrics = false (default). When set to true, additional monitoring data is collected, and a higher load is placed on the Source cluster(s) during collection.
monitoring_version: No default. Can be specified as either Major.Minor version (such as 7.3) or Major.Minor.Patch version (such as 7.3.25)
sample_queries = true (default): Controls whether the queries run on the Source cluster(s) also include the entire query text (from information_schema.mv_queries). As query sampling is enabled by default, specifying a value of false will not collect query text.

Pipelines DDL

Run the following in the SQL Editor in Studio, or your favorite SQL client.

Note: You must edit exporter-host and port in the following SQL statements to align with where your exporter process resides.

The exporter-host is typically the host of your Source cluster’s Master Aggregator that’s running the exporter, and must include http://.
The default port for the endpoint is 9104.
The IP address provided in the exporter-host argument must be resolvable by all hosts in the cluster. If the cluster you are monitoring has hosts that contain leaf nodes (as is common in a multi-host vs. single-host deployment), do not use localhost. Instead, provide the explicit IP address or hostname that the other hosts in the cluster can resolve.

Start the metrics pipeline.

CREATE OR REPLACE PIPELINE metrics.metrics AS
LOAD DATA prometheus_exporter 
"http://<exporter-host>:<exporter-port>/cluster-metrics"
CONFIG '{"is_memsql_internal":true, "high_cardinality_metrics":false, 
"monitoring_version":"<SingleStoreDB version of the 'metrics' cluster>"}' 
batch_interval 15000
INTO PROCEDURE `load_metrics` FORMAT JSON;

START PIPELINE IF NOT RUNNING metrics.metrics;

Start the blobs pipeline.

CREATE OR REPLACE PIPELINE metrics.blobs AS
LOAD DATA prometheus_exporter 
"http://<exporter-host>:<exporter-port>/samples"
CONFIG '{"is_memsql_internal":true,
"download_type":"samples", "sample_queries":true,
"monitoring_version":"<SingleStoreDB version of the metrics cluster>"}'
batch_interval 15000
INTO PROCEDURE `load_blobs` FORMAT JSON;

START PIPELINE IF NOT RUNNING metrics.blobs;

How to Stop the Monitoring Process

You may stop the monitoring process at any time by manually stopping the pipelines created earlier.

STOP PIPELINE metrics;

STOP PIPELINE blobs;

In this section:

Configure Cluster Monitoring with the Operator

Configure the Exporter Process

Configure the Metrics Database

Determine the Hostname of the Exporter

Configure the Metrics Database with the Tools Pod

Note

Create and Apply the Tools RBAC

Create and Apply the Start Monitoring Job

With Internet Access

Without Internet Access

Confirm the Start Monitoring Job is Running

Configure the Metrics Database without the Tools Pod

Note

metrics Database DDL

View the metrics Database DDL

metrics Database DDL Variables

Pipelines DDL

How to Stop the Monitoring Process

Search results

`metrics` Database DDL

View the `metrics` Database DDL

`metrics` Database DDL Variables