return [slice.name for slice in slices]
- def compose_query(self, slice=None, site=None, node=None, service=None, timeBucket="60", avg=[], sum=[], count=[], computed=[], val=[], groupBy=["Time"], orderBy=["Time"], tableName="demoevents", latest=False, max_age=60*60):
- max_age = max_age * 1000
- tablePart = "[%s.%s@-%d--1]" % ("vicci", tableName, max_age)
+ def compose_query(self, slice=None, site=None, node=None, service=None, timeBucket="60", avg=[], sum=[], count=[], computed=[], val=[], groupBy=["Time"], orderBy=["Time"], tableName="demoevents", latest=False, maxAge=60*60):
+ maxAge = maxAge * 1000
+ tablePart = "[%s.%s@-%d--1]" % ("vicci", tableName, maxAge)
fields = []
fieldNames = []
format = req.GET.get("format", "json_dicts")
- timeField = req.GET.get("timeBucket", "60")
+ timeBucket = int(req.GET.get("timeBucket", 60))
avg = self.get_list_from_req(req, "avg")
sum = self.get_list_from_req(req, "sum")
count = self.get_list_from_req(req, "count")
maxRows = req.GET.get("maxRows", None)
mergeDataModelSites = req.GET.get("mergeDataModelSites", None)
+ maxAge = int(req.GET.get("maxAge", 60*60))
+
cached = req.GET.get("cached", None)
- q = self.compose_query(slice, site, node, service, timeField, avg, sum, count, computed, [], groupBy, orderBy)
+ q = self.compose_query(slice, site, node, service, timeBucket, avg, sum, count, computed, [], groupBy, orderBy, maxAge=maxAge)
print q
<script type="text/javascript">
var options = {
-\r width: 600,\r
- height: 400,\r
- showRowNumber: false,\r
- pages: true,\r
- numRows: 9,\r
- backgroundColor: "black"\r
- };\r
-\r
- // ask django for a data source URL to use for the graphs\r
-\r
- function updateDataSourceUrl() {\r
- var sliceName = $("#historical_slicename :selected").text();\r
- var queryString = "/analytics/bigquery/?sum=@bytes_sent&avg=@cpu&groupBy=Time,city,@hostname,@site&slice=" + sliceName;\r
-\r
- $.ajax({\r
- url: queryString,\r
- dataType: 'json',\r
- type: 'GET',\r
- success: function (newData) {\r
- sendAndDraw(newData["dataSourceUrl"])\r
- }\r
- });\r
- }\r
-\r
- TIME_COL = 0;\r
- BANDWIDTH_COL = 2;\r
- CPU_COL = 1;\r
- CITY_COL = 3;\r
- NODE_COL = 4;\r
- SITE_COL = 5;\r
-\r
- google.setOnLoadCallback(function () {\r
- $('#historical_slicename').change(function()\r
- {\r
- updateDataSourceUrl();\r
- });\r
-\r
- updateDataSourceUrl();\r
- });\r
-\r
- function showSiteTimeAgg(dt) {\r
- var lineChart = new google.visualization.ChartWrapper({\r
- 'chartType': 'LineChart',\r
- 'containerId': 'chart-site-time',\r
- 'options': {\r
- 'width': 320,\r
- 'height': 300,\r
- 'title': 'Network-wide usage',\r
- 'pages': true,\r
- 'numRows': 9\r
- },\r
- 'view': {\r
- 'columns': [0, 1, 2]\r
- }\r
- });\r
- lineChart.setDataTable(dt);\r
- lineChart.draw();\r
- }\r
-\r
- function showSiteAgg(dt) {\r
- var barChart = new google.visualization.ChartWrapper({\r
- 'chartType': 'ColumnChart',\r
- 'containerId': 'chart-site-agg',\r
- 'options': {\r
- 'width': 670,\r
- 'height': 300,\r
- 'title': 'Site-wise usage',\r
- 'pages': true,\r
- 'numRows': 9\r
- },\r
- 'view': {\r
- 'columns': [1, 2, 3]\r
- }\r
- });\r
- barChart.setDataTable(dt);\r
- barChart.draw();\r
- var geoChart = new google.visualization.ChartWrapper({\r
- 'chartType': 'GeoChart',\r
- 'containerId': 'chart-geo',\r
- 'options': {\r
- 'width': 320,\r
- 'height': 300,\r
- 'displayMode': 'markers',\r
- 'region': '021',\r
- 'title': 'Usage map',\r
- colorAxis: {\r
- colors: ['green', 'purple', 'red']\r
- }\r
- },\r
- 'view': {\r
- 'columns': [0, 2, 3]\r
- }\r
- });\r
- geoChart.setDataTable(dt);\r
- geoChart.draw();\r
-\r
-/* var histogram = new google.visualization.ChartWrapper({\r
- 'chartType': 'Histogram',\r
- 'containerId': 'chart-histo',\r
- 'options': {\r
- 'width': 300,\r
- 'height': 300,\r
- },\r
- 'title': 'Sites by load',\r
- 'view': {\r
- 'columns': [1, 2]\r
- }\r
- });\r
- histogram.setDataTable(dt);\r
- histogram.draw(); */\r
-\r
- }\r
-\r
- function handleResponse(response) {\r
- var timeSlider = new google.visualization.ControlWrapper({\r
- 'controlType': 'DateRangeFilter',\r
- 'containerId': 'control1',\r
- 'options': {\r
- 'filterColumnLabel': 'Time',\r
- ui: {\r
- ticks: 10,\r
- step: "minute"\r
- }\r
- }\r
- });\r
-\r
- var categoryPicker = new google.visualization.ControlWrapper({\r
- 'controlType': 'CategoryFilter',\r
- 'allowMultiple': true,\r
- 'containerId': 'control2',\r
- 'options': {\r
- 'filterColumnLabel': 'site',\r
- 'ui': {\r
- 'labelStacking': 'vertical',\r
- 'allowTyping': false\r
- }\r
- }\r
- });\r
-\r
- var proxy = new google.visualization.ChartWrapper({\r
- 'chartType': 'Table',\r
- 'containerId': 'chart7',\r
- 'options': {\r
- 'width': 800,\r
- 'height': 300,\r
- pageSize: 5,\r
- page: 'enable',\r
- 'legend': 'none',\r
- 'title': 'Nodes'\r
- },\r
- 'view': {\r
- 'columns': [0, 1, 2, 3, 4, 5]\r
- }\r
- });\r
-\r
- function avg_bandwidth(arr) {\r
+\r width: 600,
+ height: 400,
+ showRowNumber: false,
+ pages: true,
+ numRows: 9,
+ backgroundColor: "black"
+ };
+
+ // ask django for a data source URL to use for the graphs
+
+ function updateDataSourceUrl() {
+ var sliceName = $("#historical_slicename :selected").text();
+ var queryString = "/analytics/bigquery/?timeBucket=600&maxAge=86400&sum=@bytes_sent&avg=@cpu&groupBy=Time,city,@hostname,@site&slice=" + sliceName;
+
+ $.ajax({
+ url: queryString,
+ dataType: 'json',
+ type: 'GET',
+ success: function (newData) {
+ sendAndDraw(newData["dataSourceUrl"])
+ }
+ });
+ }
+
+ TIME_COL = 0;
+ BANDWIDTH_COL = 2;
+ CPU_COL = 1;
+ CITY_COL = 3;
+ NODE_COL = 4;
+ SITE_COL = 5;
+
+ google.setOnLoadCallback(function () {
+ $('#historical_slicename').change(function()
+ {
+ updateDataSourceUrl();
+ });
+
+ updateDataSourceUrl();
+ });
+
+ function showSiteTimeAgg(dt) {
+ var lineChart = new google.visualization.ChartWrapper({
+ 'chartType': 'LineChart',
+ 'containerId': 'chart-site-time',
+ 'options': {
+ 'width': 320,
+ 'height': 300,
+ 'title': 'Network-wide usage',
+ 'pages': true,
+ 'numRows': 9
+ },
+ 'view': {
+ 'columns': [0, 1, 2]
+ }
+ });
+ lineChart.setDataTable(dt);
+ lineChart.draw();
+ }
+
+ function showSiteAgg(dt) {
+ var barChart = new google.visualization.ChartWrapper({
+ 'chartType': 'ColumnChart',
+ 'containerId': 'chart-site-agg',
+ 'options': {
+ 'width': 670,
+ 'height': 300,
+ 'title': 'Site-wise usage',
+ 'pages': true,
+ 'numRows': 9
+ },
+ 'view': {
+ 'columns': [1, 2, 3]
+ }
+ });
+ barChart.setDataTable(dt);
+ barChart.draw();
+ var geoChart = new google.visualization.ChartWrapper({
+ 'chartType': 'GeoChart',
+ 'containerId': 'chart-geo',
+ 'options': {
+ 'width': 320,
+ 'height': 300,
+ 'displayMode': 'markers',
+ 'region': '021',
+ 'title': 'Usage map',
+ colorAxis: {
+ colors: ['green', 'purple', 'red']
+ }
+ },
+ 'view': {
+ 'columns': [0, 2, 3]
+ }
+ });
+ geoChart.setDataTable(dt);
+ geoChart.draw();
+
+/* var histogram = new google.visualization.ChartWrapper({
+ 'chartType': 'Histogram',
+ 'containerId': 'chart-histo',
+ 'options': {
+ 'width': 300,
+ 'height': 300,
+ },
+ 'title': 'Sites by load',
+ 'view': {
+ 'columns': [1, 2]
+ }
+ });
+ histogram.setDataTable(dt);
+ histogram.draw(); */
+
+ }
+
+ function handleResponse(response) {
+ var timeSlider = new google.visualization.ControlWrapper({
+ 'controlType': 'DateRangeFilter',
+ 'containerId': 'control1',
+ 'options': {
+ 'filterColumnLabel': 'Time',
+ ui: {
+ ticks: 10,
+ step: "minute"
+ }
+ }
+ });
+
+ var categoryPicker = new google.visualization.ControlWrapper({
+ 'controlType': 'CategoryFilter',
+ 'allowMultiple': true,
+ 'containerId': 'control2',
+ 'options': {
+ 'filterColumnLabel': 'site',
+ 'ui': {
+ 'labelStacking': 'vertical',
+ 'allowTyping': false
+ }
+ }
+ });
+
+ var proxy = new google.visualization.ChartWrapper({
+ 'chartType': 'Table',
+ 'containerId': 'chart7',
+ 'options': {
+ 'width': 800,
+ 'height': 300,
+ pageSize: 5,
+ page: 'enable',
+ 'legend': 'none',
+ 'title': 'Nodes'
+ },
+ 'view': {
+ 'columns': [0, 1, 2, 3, 4, 5]
+ }
+ });
+
+ function avg_bandwidth(arr) {
var ret = 0;
for (var i = 0; i < arr.length; i++) {
ret+=arr[i]*8.0/1024.0/1024.0/1024.0;
return 0;
}
return ret/arr.length;
- }\r
-\r
- function sum_bytes_sent_as_bw(arr) {\r
+ }
+
+ function sum_bytes_sent_as_bw(arr) {
var ret = 0;
for (var i = 0; i < arr.length; i++) {
ret+=arr[i]*8.0/1024.0/1024.0/1024.0;
}
return ret/60.0;
- }\r
-\r
- function sum_bytes_sent_as_GB(arr) {\r
+ }
+
+ function sum_bytes_sent_as_GB(arr) {
var ret = 0;
for (var i = 0; i < arr.length; i++) {
ret+=arr[i]/1024.0/1024.0/1024.0;
}
return ret;
- }\r
-\r
- function fixDate2(unixDate) {\r
- // not completely sure why we have to do this, as the data was in\r
- // javascript Date() objects to start with. If we don't do it,\r
- // then the horizontal axis will be blank.\r
+ }
+
+ function fixDate2(unixDate) {
+ // not completely sure why we have to do this, as the data was in
+ // javascript Date() objects to start with. If we don't do it,
+ // then the horizontal axis will be blank.
return new Date(unixDate);
- }\r
-\r
- var format0dp = new google.visualization.NumberFormat({fractionDigits:0});\r
- var format2dp = new google.visualization.NumberFormat({fractionDigits:2});\r
-\r
- // Create a group for charts that will have a horizontal axis that is\r
- // time.\r
-\r
- google.visualization.events.addListener(proxy, 'ready', function () {\r
- var dt = proxy.getDataTable();\r
- var groupedData1 = google.visualization.data.group(dt, [{\r
+ }
+
+ var format0dp = new google.visualization.NumberFormat({fractionDigits:0});
+ var format2dp = new google.visualization.NumberFormat({fractionDigits:2});
+
+ // Create a group for charts that will have a horizontal axis that is
+ // time.
+
+ google.visualization.events.addListener(proxy, 'ready', function () {
+ var dt = proxy.getDataTable();
+ var groupedData1 = google.visualization.data.group(dt, [{
column: TIME_COL,
type: 'datetime',
modifier: fixDate2,
- }], [{\r
- column: CPU_COL,\r
- type: 'number',\r
- label: "avg cpu",\r
- aggregation: google.visualization.data.avg\r
- }, {\r
- column: BANDWIDTH_COL,\r
- type: 'number',\r
- label: "Gbps",\r
- aggregation: sum_bytes_sent_as_bw\r
- }]);\r
-\r
- format0dp.format(groupedData1,1);\r
- format2dp.format(groupedData1,2);\r
-\r
- showSiteTimeAgg(groupedData1);\r
- });\r
-\r
- // Create a group for charts that will have a horizontal axis that is\r
- // city or site.\r
-\r
- google.visualization.events.addListener(proxy, 'ready', function () {\r
- var dt = proxy.getDataTable();\r
- var groupedData0 = google.visualization.data.group(dt, [CITY_COL, SITE_COL], [{\r
- column: CPU_COL,\r
- type: 'number',\r
- label: 'avg cpu',\r
- aggregation: google.visualization.data.avg\r
- }, {\r
- column: BANDWIDTH_COL,\r
- type: 'number',\r
- label: "GB sent",\r
- aggregation: sum_bytes_sent_as_GB\r
- }]);\r
-\r
- format0dp.format(groupedData0,2);\r
- format2dp.format(groupedData0,3);\r
-\r
- showSiteAgg(groupedData0);\r
- });\r
-\r
- data = response.getDataTable();\r
- new google.visualization.Dashboard(document.getElementById('dashboard')).\r
- // Establish bindings, declaring the both the slider and the category\r
- // picker will drive both charts.\r
- bind([categoryPicker, timeSlider], [proxy]).\r
- // Draw the entire dashboard.\r
- draw(data);\r
-\r
- }\r
-\r
- function sendAndDraw(queryString) {\r
- query = new google.visualization.Query(queryString)\r
- query && query.abort();\r
- query.send(function (response) {\r
- handleResponse(response);\r
- });\r
+ }], [{
+ column: CPU_COL,
+ type: 'number',
+ label: "avg cpu",
+ aggregation: google.visualization.data.avg
+ }, {
+ column: BANDWIDTH_COL,
+ type: 'number',
+ label: "Gbps",
+ aggregation: sum_bytes_sent_as_bw
+ }]);
+
+ format0dp.format(groupedData1,1);
+ format2dp.format(groupedData1,2);
+
+ showSiteTimeAgg(groupedData1);
+ });
+
+ // Create a group for charts that will have a horizontal axis that is
+ // city or site.
+
+ google.visualization.events.addListener(proxy, 'ready', function () {
+ var dt = proxy.getDataTable();
+ var groupedData0 = google.visualization.data.group(dt, [CITY_COL, SITE_COL], [{
+ column: CPU_COL,
+ type: 'number',
+ label: 'avg cpu',
+ aggregation: google.visualization.data.avg
+ }, {
+ column: BANDWIDTH_COL,
+ type: 'number',
+ label: "GB sent",
+ aggregation: sum_bytes_sent_as_GB
+ }]);
+
+ format0dp.format(groupedData0,2);
+ format2dp.format(groupedData0,3);
+
+ showSiteAgg(groupedData0);
+ });
+
+ data = response.getDataTable();
+ new google.visualization.Dashboard(document.getElementById('dashboard')).
+ // Establish bindings, declaring the both the slider and the category
+ // picker will drive both charts.
+ bind([categoryPicker, timeSlider], [proxy]).
+ // Draw the entire dashboard.
+ draw(data);
+
+ }
+
+ function sendAndDraw(queryString) {
+ query = new google.visualization.Query(queryString)
+ query && query.abort();
+ query.send(function (response) {
+ handleResponse(response);
+ });
}
</script>
git://git.onelab.eu / plstackapi.git / commitdiff