Spark应用监控解决方案--使用Prometheus和Grafana监控Spark应用

其他 2019-08-29 17:14:43 阅读次数: 0

Spark任务启动后，我们通常都是通过跳板机去Spark UI界面查看对应任务的信息，一旦任务多了之后，这将会是让人头疼的问题。如果能将所有任务信息集中起来监控，那将会是很完美的事情。

通过Spark官网指导文档，发现Spark只支持以下sink

Each instance can report to zero or more sinks. Sinks are contained in the org.apache.spark.metrics.sink package:

  • ConsoleSink: Logs metrics information to the console.
  • CSVSink: Exports metrics data to CSV files at regular intervals.
  • JmxSink: Registers metrics for viewing in a JMX console.
  • MetricsServlet: Adds a servlet within the existing Spark UI to serve metrics data as JSON data.
  • GraphiteSink: Sends metrics to a Graphite node.
  • Slf4jSink: Sends metrics to slf4j as log entries.
  • StatsdSink: Sends metrics to a StatsD node.

 

没有比较常用的Influxdb和Prometheus ~~~

谷歌一把发现要支持influxdb需要使用第三方包，比较有参考意义的是这篇，Monitoring Spark Streaming with InfluxDB and Grafana ,在提交任务的时候增加file和配置文件，但成功永远不会这么轻松。。。

写入influxdb的数据都是以application_id命名的，类似这种application_1533838659288_1030_1_jvm_heap_usage，也就是说每个任务的指标都是在单独的表，最终我们展示在grafana不还得一个一个配置么？

显然这个不是我想要的结果，最终目的就是：一次配置后每提交一个任务自动会在监控上看到。

谷歌是治愈一切的良药，终究找到一个比较完美的解决方案，就是通过graphite_exporter中转数据后接入Prometheus，再通过grafana展示出来。

所以，目前已经实践可行的方案有两个

方案一：

监控数据直接写入influxdb，再通过grafana读取数据做展示，步骤如下：

1.在spark下 conf/metrics.properties 加入以下配置

master.source.jvm.class=org.apache.spark.metrics.source.JvmSource
worker.source.jvm.class=org.apache.spark.metrics.source.JvmSource
driver.source.jvm.class=org.apache.spark.metrics.source.JvmSourc
executor.source.jvm.class=org.apache.spark.metrics.source.JvmSource

*.sink.influx.class=org.apache.spark.metrics.sink.InfluxDbSink
*.sink.influx.protocol=http
*.sink.influx.host=xx.xx.xx.xx
*.sink.influx.port=8086
*.sink.influx.database=sparkonyarn
*.sink.influx.auth=admin:admin

2.在提交任务的时候增加以下配置，并确保以下jar存在

--files /spark/conf/metrics.properties \

--conf spark.metrics.conf=metrics.properties \
--jars /spark/jars/metrics-influxdb-1.1.8.jar,/spark/jars/spark-influx-sink-0.4.0.jar \
--conf spark.driver.extraClassPath=metrics-influxdb-1.1.8.jar:spark-influx-sink-0.4.0.jar \
--conf spark.executor.extraClassPath=metrics-influxdb-1.1.8.jar:spark-influx-sink-0.4.0.jar

缺点：application_id发生变化需要重新配置grafana

 

方案二（目前在用的）：

通过graphite_exporter将原生数据通过映射文件转化为有 label 维度的 Prometheus 数据

1.下载graphite_exporter，解压后执行以下命令，其中graphite_exporter_mapping需要我们自己创建，内容为数据映射文件

 nohup ./graphite_exporter --graphite.mapping-config=graphite_exporter_mapping &  

例如

 

mappings:
- match: '*.*.jvm.*.*'
  name: jvm_memory_usage
  labels:
    application: $1
    executor_id: $2
    mem_type: $3 qty: $4

会将数据转化成 metric name 为 jvm_memory_usage，label 为 application，executor_id，mem_type，qty 的格式。

application_1533838659288_1030_1_jvm_heap_usage -> jvm_memory_usage{application="application_1533838659288_1030",executor_id="driver",mem_type="heap",qty="usage"}

2.配置 Prometheus 从 graphite_exporter 获取数据，重启prometheus
/path/to/prometheus/prometheus.yml
scrape_configs:
  - job_name: 'spark'
    static_configs:
    - targets: ['localhost:9108']

3.在spark下 conf/metrics.properties 加入以下配置

master.source.jvm.class=org.apache.spark.metrics.source.JvmSource
worker.source.jvm.class=org.apache.spark.metrics.source.JvmSource
driver.source.jvm.class=org.apache.spark.metrics.source.JvmSourc
executor.source.jvm.class=org.apache.spark.metrics.source.JvmSource

*.sink.graphite.class=org.apache.spark.metrics.sink.GraphiteSink
*.sink.graphite.protocol=tcp
*.sink.graphite.host=xx.xx.xx.xx
*.sink.graphite.port=9109
*.sink.graphite.period=5
*.sink.graphite.unit=seconds

4.提交spark任务的时候增加  --files /spark/conf/metrics.properties

5.最后在grafana创建prometheus数据源，创建需要的指标，最终效果如下，有新提交的任务不需要再配置监控，直接选择application_id就可以看对应的信息

 

需要用到的jar包

https://repo1.maven.org/maven2/com/izettle/metrics-influxdb/1.1.8/metrics-influxdb-1.1.8.jar

https://mvnrepository.com/artifact/com.palantir.spark.influx/spark-influx-sink

 

模板 

mappings:
- match: '*.*.executor.filesystem.*.*'
  name: filesystem_usage
  labels:
    application: $1
    executor_id: $2
    fs_type: $3
    qty: $4

- match: '*.*.executor.threadpool.*'
  name: executor_tasks
  labels:
    application: $1
    executor_id: $2
    qty: $3

- match: '*.*.executor.jvmGCTime.count'
  name: jvm_gcTime_count
  labels:
    application: $1
    executor_id: $2

- match: '*.*.executor.*.*'
  name: executor_info
  labels:
    application: $1
    executor_id: $2
    type: $3
    qty: $4

- match: '*.*.jvm.*.*'
  name: jvm_memory_usage
  labels:
    application: $1
    executor_id: $2
    mem_type: $3
    qty: $4

- match: '*.*.jvm.pools.*.*'
  name: jvm_memory_pools
  labels:
    application: $1
    executor_id: $2
    mem_type: $3
    qty: $4

- match: '*.*.BlockManager.*.*'
  name: block_manager
  labels:
    application: $1
    executor_id: $2
    type: $3
    qty: $4

- match: '*.driver.DAGScheduler.*.*'
  name: DAG_scheduler
  labels:
    application: $1
    type: $2
    qty: $3

- match: '*.driver.*.*.*.*'
  name: task_info
  labels:
    application: $1
    task: $2
    type1: $3
    type2: $4
    qty: $5
graphite_exporter_mapping

 

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  "annotations": {
    "list": [
      {
        "builtIn": 1,
        "datasource": "-- Grafana --",
        "enable": true,
        "hide": true,
        "iconColor": "rgba(0, 211, 255, 1)",
        "name": "Annotations & Alerts",
        "type": "dashboard"
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  "id": 6,
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      "panels": [],
      "title": "Batch Info",
      "type": "row"
    },
    {
      "cacheTimeout": null,
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      "colorValue": true,
      "colors": [
        "#73BF69",
        "rgba(237, 129, 40, 0.89)",
        "#d44a3a"
      ],
      "datasource": "SparkFromGraphite",
      "format": "none",
      "gauge": {
        "maxValue": 100,
        "minValue": 0,
        "show": false,
        "thresholdLabels": false,
        "thresholdMarkers": true
      },
      "gridPos": {
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        "x": 0,
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      },
      "id": 44,
      "interval": "30s",
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      "mappingType": 1,
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        }
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      "maxDataPoints": 100,
      "nullPointMode": "connected",
      "nullText": null,
      "options": {},
      "pluginVersion": "6.2.5",
      "postfix": "",
      "postfixFontSize": "50%",
      "prefix": "",
      "prefixFontSize": "50%",
      "rangeMaps": [
        {
          "from": "null",
          "text": "N/A",
          "to": "null"
        }
      ],
      "sparkline": {
        "fillColor": "rgba(31, 118, 189, 0.18)",
        "full": false,
        "lineColor": "rgb(31, 120, 193)",
        "show": false
      },
      "tableColumn": "",
      "targets": [
        {
          "expr": "task_info{type1=\"StreamingMetrics\",type2=\"streaming\", application=\"$application_ID\",qty=\"totalCompletedBatches\"}",
          "format": "time_series",
          "instant": false,
          "interval": "",
          "intervalFactor": 1,
          "legendFormat": "{{totalCompletedBatches}}",
          "refId": "A"
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      "thresholds": "#73BF69",
      "timeFrom": null,
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      "datasource": "SparkFromGraphite",
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      },
      "tableColumn": "",
      "targets": [
        {
          "expr": "task_info{type1=\"StreamingMetrics\",type2=\"streaming\", application=\"$application_ID\",qty=\"totalProcessedRecords\"}",
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          "legendFormat": "{{qty}}",
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      "thresholds": "#299c46",
      "timeFrom": null,
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    },
    {
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      ],
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        "show": false
      },
      "tableColumn": "",
      "targets": [
        {
          "expr": "task_info{type1=\"StreamingMetrics\",type2=\"streaming\", application=\"$application_ID\",qty=\"waitingBatches\"}",
          "format": "time_series",
          "intervalFactor": 1,
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      "renderer": "flot",
      "seriesOverrides": [],
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          "datasource": "SparkFromGraphite",
          "editable": true,
          "error": false,
          "fill": 1,
          "grid": {},
          "gridPos": {
            "h": 7,
            "w": 12,
            "x": 12,
            "y": 25
          },
          "id": 26,
          "legend": {
            "avg": false,
            "current": false,
            "max": false,
            "min": false,
            "show": true,
            "total": false,
            "values": false
          },
          "lines": true,
          "linewidth": 1,
          "links": [],
          "nullPointMode": "connected",
          "options": {},
          "percentage": false,
          "pointradius": 5,
          "points": false,
          "renderer": "flot",
          "seriesOverrides": [
            {
              "alias": "total",
              "linewidth": 4,
              "yaxis": 1
            }
          ],
          "spaceLength": 10,
          "stack": false,
          "steppedLine": false,
          "targets": [
            {
              "expr": "filesystem_usage{qty=\"write_bytes\", fs_type=\"hdfs\", application=\"$application_ID\"}",
              "format": "time_series",
              "hide": false,
              "intervalFactor": 2,
              "legendFormat": "{{executor_id}}",
              "metric": "filesystem_usage",
              "refId": "A",
              "step": 2,
              "target": ""
            },
            {
              "expr": "sum(filesystem_usage{qty=\"write_bytes\", fs_type=\"hdfs\", application=\"$application_ID\"})",
              "format": "time_series",
              "intervalFactor": 1,
              "legendFormat": "total",
              "refId": "B"
            }
          ],
          "thresholds": [],
          "timeFrom": null,
          "timeRegions": [],
          "timeShift": null,
          "title": "Executor HDFS Writes (Stacked)",
          "tooltip": {
            "shared": true,
            "sort": 0,
            "value_type": "cumulative"
          },
          "type": "graph",
          "xaxis": {
            "buckets": null,
            "mode": "time",
            "name": null,
            "show": true,
            "values": []
          },
          "yaxes": [
            {
              "format": "decbytes",
              "logBase": 1,
              "max": null,
              "min": 0,
              "show": true
            },
            {
              "format": "short",
              "logBase": 1,
              "max": null,
              "min": null,
              "show": true
            }
          ],
          "yaxis": {
            "align": false,
            "alignLevel": null
          }
        }
      ],
      "title": "HDFS Bytes Reads/Writes Per Executor",
      "type": "row"
    }
  ],
  "refresh": false,
  "schemaVersion": 18,
  "style": "dark",
  "tags": [],
  "templating": {
    "list": [
      {
        "allFormat": "glob",
        "allValue": null,
        "current": {
          "text": "application_1566481621886_138866",
          "value": "application_1566481621886_138866"
        },
        "datasource": "SparkFromGraphite",
        "definition": "label_values(application)",
        "hide": 0,
        "includeAll": false,
        "label": "",
        "multi": false,
        "multiFormat": "glob",
        "name": "application_ID",
        "options": [],
        "query": "label_values(application)",
        "refresh": 1,
        "refresh_on_load": false,
        "regex": "",
        "skipUrlSync": false,
        "sort": 2,
        "tagValuesQuery": "",
        "tags": [],
        "tagsQuery": "",
        "type": "query",
        "useTags": false
      }
    ]
  },
  "time": {
    "from": "now-12h",
    "to": "now"
  },
  "timepicker": {
    "now": true,
    "refresh_intervals": [
      "5s",
      "10s",
      "30s",
      "1m",
      "5m",
      "15m",
      "30m",
      "1h",
      "2h",
      "1d"
    ],
    "time_options": [
      "5m",
      "15m",
      "1h",
      "6h",
      "12h",
      "24h",
      "2d",
      "7d",
      "30d"
    ]
  },
  "timezone": "browser",
  "title": "Spark-on-Yarn",
  "uid": "yJ1JPHTiz",
  "version": 40
}
spark_prometheus_metrics

 

参考资料

https://github.com/palantir/spark-influx-sink

https://spark.apache.org/docs/latest/monitoring.html

https://www.linkedin.com/pulse/monitoring-spark-streaming-influxdb-grafana-christian-g%C3%BCgi

https://github.com/prometheus/prometheus/wiki/Default-port-allocations

https://github.com/prometheus/graphite_exporter

https://prometheus.io/download/

https://rokroskar.github.io/monitoring-spark-on-hadoop-with-prometheus-and-grafana.html

https://blog.csdn.net/lsshlsw/article/details/82670508

https://www.jianshu.com/p/274380bb0974

 

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