Add Kibana visualizations examples for NDR result
[nfvbench.git] / kibana / visualizations / ndr_capacity_pps_theoretical_scatter_plot.json
diff --git a/kibana/visualizations/ndr_capacity_pps_theoretical_scatter_plot.json b/kibana/visualizations/ndr_capacity_pps_theoretical_scatter_plot.json
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+{
+  $schema: "https://vega.github.io/schema/vega-lite/v2.json"
+  title: "Capacity in Mpps - 0,001% loss ratio"
+  data: {
+    url: {
+      %context%: true
+      %timefield%: "@timestamp"
+      index: resu*
+      body: {
+        _source: ["@timestamp", "_source", "rate_pps", "theoretical_tx_rate_pps", "flow_count", "frame_size", "user_label"]
+      },
+      size: 10000
+    },
+    format: { property: "hits.hits" }
+  },
+  transform: [
+    { calculate: "datum._source['rate_pps'] / 1000000" as: "rate_pps"},
+        { calculate: "datum._source['theoretical_tx_rate_pps'] / 1000000" as: "theoretical_tx_rate_pps"},
+    { calculate: "datum._source['flow_count']" as: "flow_count"},
+    { calculate: "isNaN(toNumber(datum._source['frame_size'])) ? 362 : toNumber(datum._source['frame_size'])" as: "frame_size"}
+    { calculate: "datum._source['user_label'] + '-' + datum._source['flow_count']" as: "label"}
+  ],
+  center: true,
+  hconcat: [
+  {
+      width:10,
+      selection: {
+        legendSel: {
+          type: "multi",
+          encodings: [ "color", "shape" ],
+          toggle: "event.shiftKey"
+        }
+      },
+      encoding: {
+        y: {
+          field: "label",
+          type: "nominal",
+          axis: {
+            title: "",
+            domain: false,
+            ticks: false,
+            offset: 10
+          },
+        },
+        color: {
+          condition: {
+            selection: "legendSel",
+            field: "label",
+            type: "nominal",
+            legend: null
+          },
+          value: "lightgrey"
+        }
+      },
+      mark: {
+        type: "square",
+        size: 120,
+        opacity: 1
+      }
+    },
+    {
+      layer: [
+        {
+          mark: {
+            type: "line",
+            tooltip: true
+          },
+          encoding: {
+            x: { field: "frame_size", type: "quantitative", title: "Frame size (bytes)", axis: {offset: 10} }
+            y: { field: "theoretical_tx_rate_pps", type: "quantitative", title: "Offered load (Mpps)" , axis: {offset: 10}  }
+            strokeDash: {"field": "theoretical_tx_rate_pps", "type": "nominal"}
+            tooltip: [{"field": "theoretical_tx_rate_pps", "type": "quantitative", title: "theoretical max capacity"}],
+            color: { "value": "red"}
+          }
+        },
+        {
+          width:500,
+          height:280,
+          transform: [
+            {filter: { selection: "legendSel"}}
+          ],
+          mark: {
+            "type": "point",
+            "tooltip": true
+          },
+          selection: {
+            grid: {
+              type: "interval",
+              resolve: "global",
+              bind: "scales",
+              translate: "[mousedown[!event.shiftKey], window:mouseup] > window:mousemove!",
+              zoom: "wheel![!event.shiftKey]"
+            },
+            pts: {
+              type: "single",
+              fields: ["label"]
+            }
+          },
+          encoding: {
+            x: {
+              field: "frame_size",
+              title: "Frame size (bytes)",
+              type: "quantitative"
+            }
+            y: {
+              field: "rate_pps",
+              title: "Offered load (Mpps)",
+              type: "quantitative"
+            }
+            color: {
+              field: "label", "type": "nominal",
+                   "legend": null
+            }
+            shape: {
+              field: "flow_count",
+              type: "nominal"
+            }
+            tooltip: {
+              "field": "rate_pps",
+              "title": "Offered load (Mpps)",
+              "type": "quantitative"
+            }
+          }
+        }
+      ]
+    }
+  ]
+}
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