Setup a Kibana dashboard for data about last Jenkins build - elasticsearch

I use Kibana to show data about automated test cases stored in a single elastic search index.
These tests can be repeated multiple times during the day and right now are identified by a build number that comes from Jenkins. So, if I want to see the latest results, I need to add a filter in my dashboards where I set the last known value of the build number.
Is there a way to automatically show in a dashboard the values about the last build?
Thank you.
EDIT: Here's a data sample:
{
"_index": "data",
"_type": "_doc",
"_id": "33rugH0B0CwJH7IcV11v",
"_score": 1,
"_source": {
"market": "FRA",
"price_code": "DIS22FREH1003",
"test_case_id": "NPM_14",
"environment": "PROD",
"cruise_id": "DI20220707CPVCP1",
"jenkins_job_name": "MonitoringNPM_14",
"#timestamp": "2021-12-03T16:34:03.360+0100",
"jenkins_job_number": 8,
"agency": "FR900000",
"fail_code": "IncorrectGuarantee",
"build_number": 8,
"category": "IR2"
},
"fields": {
"environment.keyword": [
"PROD"
],
"test_case_id": [
"NPM_14"
],
"category.keyword": [
"IR2"
],
"price_code": [
"DIS22FREH1003"
],
"cruise_id": [
"DI20220707CPVCP1"
],
"price_code.keyword": [
"DIS22FREH1003"
],
"agency": [
"FR900000"
],
"jenkins_job_number": [
"8"
],
"agency.keyword": [
"FR900000"
],
"jenkins_job_number.keyword": [
"8"
],
"market": [
"FRA"
],
"jenkins_job_name.keyword": [
"MonitoringNPM_14"
],
"test_case_id.keyword": [
"NPM_14"
],
"environment": [
"PROD"
],
"#timestamp": [
"2021-12-03T15:34:03.360Z"
],
"jenkins_job_name": [
"MonitoringNPM_14"
],
"fail_code.keyword": [
"IncorrectGuarantee"
],
"fail_code": [
"IncorrectGuarantee"
],
"build_number": [
8
],
"market.keyword": [
"FRA"
],
"cruise_id.keyword": [
"DI20220707CPVCP1"
],
"category": [
"IR2"
]
}
}

Related

To index geojson data to elasticsearch using curl

I'd like to index a geojson data to elasticsearch using curl
The geojson data looks like this:
{
"type": "FeatureCollection",
"name": "telco_new_development",
"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } },
"features": [
{ "type": "Feature", "properties": { "ogc_fid": 1, "name": "Yarrabilba", "carrier_name": "OptiComm", "uid": "35", "development_name": "Yarrabilba", "stage": "None", "developer_name": "Refer to Carrier", "development_nature": "Residential", "development_type": "Sub-division", "estimated_number_of_lots_or_units": "18500", "status": "Ready for service", "developer_application_date": "Check with carrier", "contract_date": "TBC", "estimated_service_date": "30 Jul 2013", "technology_type": "FTTP", "last_modified_date": "8 Jul 2020" }, "geometry": { "type": "MultiPolygon", "coordinates": [ [ [ [ 153.101112, -27.797998 ], [ 153.09786, -27.807122 ], [ 153.097715, -27.816313 ], [ 153.100598, -27.821068 ], [ 153.103789, -27.825047 ], [ 153.106079, -27.830225 ], [ 153.108248, -27.836107 ], [ 153.110692, -27.837864 ], [ 153.116288, -27.840656 ], [ 153.119923, -27.844818 ], [ 153.122317, -27.853523 ], [ 153.127785, -27.851777 ], [ 153.131234, -27.85115 ], [ 153.135634, -27.849741 ], [ 153.138236, -27.848668 ], [ 153.141703, -27.847075 ], [ 153.152205, -27.84496 ], [ 153.155489, -27.843381 ], [ 153.158613, -27.841546 ], [ 153.161937, -27.84059 ], [ 153.156361, -27.838492 ], [ 153.157097, -27.83451 ], [ 153.15036, -27.832705 ], [ 153.151126, -27.827536 ], [ 153.15169, -27.822564 ], [ 153.148492, -27.820801 ], [ 153.148375, -27.817969 ], [ 153.139019, -27.815804 ], [ 153.139814, -27.808556 ], [ 153.126486, -27.80576 ], [ 153.124679, -27.803584 ], [ 153.120764, -27.802953 ], [ 153.121397, -27.797353 ], [ 153.100469, -27.79362 ], [ 153.099828, -27.793327 ], [ 153.101112, -27.797998 ] ] ] ] } },
{ "type": "Feature", "properties": { "ogc_fid": 2, "name": "Elliot Springs", "carrier_name": "OptiComm", "uid": "63", "development_name": "Elliot Springs", "stage": "None", "developer_name": "Refer to Carrier", "development_nature": "Residential", "development_type": "Sub-division", "estimated_number_of_lots_or_units": "11674", "status": "Ready for service", "developer_application_date": "Check with carrier", "contract_date": "TBC", "estimated_service_date": "29 Nov 2018", "technology_type": "FTTP", "last_modified_date": "8 Jul 2020" }, "geometry": { "type": "MultiPolygon", "coordinates": [ [ [ [ 146.862725, -19.401424 ], [ 146.865987, -19.370253 ], [ 146.872767, -19.370901 ], [ 146.874484, -19.354706 ], [ 146.874913, -19.354301 ], [ 146.877059, -19.356811 ], [ 146.87972, -19.35835 ], [ 146.889161, -19.359321 ], [ 146.900062, -19.367581 ], [ 146.884955, -19.38507 ], [ 146.88341, -19.402558 ], [ 146.862725, -19.401424 ] ] ] ] } },
...
However, my curl is returns an error called The bulk request must be terminated by a newline [\\n]
curl -H 'Content-Type: application/x-ndjson' -XPOST 'localhost:9200/geo/building/_bulk?pretty' --data-binary #building.geojson
{
"error" : {
"root_cause" : [
{
"type" : "illegal_argument_exception",
"reason" : "The bulk request must be terminated by a newline [\\n]"
}
],
"type" : "illegal_argument_exception",
"reason" : "The bulk request must be terminated by a newline [\\n]"
},
"status" : 400
}
Any suggestion?
your format is not suitable for _bulk like that, as it's missing the structure it expects. https://www.elastic.co/guide/en/elasticsearch/reference/current/docs-bulk.html goes into that
you need;
to update your json file to have something like { "index" : { "_index" : "INDEX-NAME-HERE" } } before each of the documents
each document also needs to be on a single line
each line needs a \n at the end of it so that the bulk API knows when the action/record ends

Elasticsearch geospatial map, not able to render Linestring

the elasticsearch index contains json as below, only relevant element is show
"geoLocation": {
"coordinates": [ [ -90.66487121582031, 42.49201965332031 ], [ -90.66487884521484, 42.49202346801758 ], [ -90.6648941040039, 42.492034912109375 ], [ -90.66490936279297, 42.49203872680664 ], [ -90.66492462158203, 42.492042541503906 ], [ -90.6649398803711, 42.49204635620117 ], [ -90.66495513916016, 42.49205017089844 ], [ -90.66497039794922, 42.4920539855957 ], [ -90.66498565673828, 42.492061614990234 ], [ -90.66500854492188, 42.492061614990234 ], [ -90.66502380371094, 42.49207305908203 ], [ -90.6650390625, 42.4920654296875 ] ],
"type": "linestring"
},
The template for generating the mapping is as below
PUT _template/template_1?include_type_name=true
{
"index_patterns": ["metromind-its-alerts-day2-*"],
"settings": {
"number_of_shards": 2
},
"mappings": {
"logs": {
"properties": {
"geoLocation": {
"type": "geo_shape"
}
}
}
}
}
the mapping generated is shown below
mapping showing the geoLocation type
When Kibana Maps are used it detects the geo_shape
Kibana Map to render Linestring
Note However no Linestring is rendered, please suggest the resolution
The line string is there, in Dubuque IL, it's just that it's extra small at the scale of the earth.
Just click on the following icon and Elastic Map will focus on it and you'll see it:

How to add a custom key-value pair to a grok pattern?

How can I add a custom key-value pair to a grok pattern?
For example, I would like to add a key-value pair of "city": [["New York]] to the data result, even though it doesn't exist in the log line.
How do I do this? Tyvm, Keith :^)
Complete, Minimal, and Verifiable Example
Data:
WARN 10/11/2017 kmiklas
Grok:
%{WORD:logLevel}\s%{DATE:date}\s%{USER:user}
{
"logLevel": [
[
"WARN"
]
],
"date": [
[
"10/11/2017"
]
],
"DATE_US": [
[
"10/11/2017"
]
],
"MONTHNUM": [
[
"10",
null
]
],
"MONTHDAY": [
[
"11",
null
]
],
"YEAR": [
[
"2017",
null
]
],
"DATE_EU": [
[
null
]
],
"user": [
[
"kmiklas"
]
],
"USERNAME": [
[
"kmiklas"
]
]
}
I understand that will be a fixed field, so you need to use the mutate method, like this:
mutate { add_field => { "city" => [["New York"]] } }
if you want the new field to be only in some logs you need to include if
if "some_test" in [message]{mutate.....}

what is the json mapping to insert geo data into elasticsearch?

what would be the json mapping to insert geo data into elasticsearch ??
if the sample json data as follows:
{ "type": "Feature", "properties": { "ID": 631861455.000000, "address": "1206 UPPER", "city": "la vegas", "state": "AL", "zip_code": "15656", "OGR_GEOMETRY": "POLYGON" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ -86.477551331, 32.490605650000099 ], [ -86.477637350999899, 32.4903921820001 ], [ -86.478257247, 32.490565591000099 ], [ -86.478250466, 32.490580239000103 ], [ -86.478243988, 32.490593680000096 ], [ -86.47823751, 32.490607122 ], [ -86.478231749, 32.490619100000096 ], [ -86.478224637, 32.490634065000101 ], [ -86.47821823699999, 32.490647540000097 ], [ -86.478211847999901, 32.490661035000095 ], [ -86.478205478999897, 32.490674526000099 ], [ -86.478202107999891, 32.490681666000093 ], [ -86.478199132, 32.4906880240001 ], [ -86.478192825999898, 32.490701523 ], [ -86.478186533, 32.490715047 ], [ -86.47818320899999, 32.490722209000097 ], [ -86.47818027999989, 32.490728569000098 ], [ -86.478174063, 32.490742125000097 ], [ -86.47816785099999, 32.490755654000097 ], [ -86.47816255799999, 32.490767236000096 ], [ -86.478159053999889, 32.490774513000105 ], [ -86.477551331, 32.490605650000099 ] ] ] } }
Look at Geo point mapping.
You need to define mapping.

Error in importing geojson polygon into RethinkDB

I have following geojson polygon JSON that I'd like to import into rethinkDB. I attempted to use following r.geojson approach to import (refer to Building an earthquake map with RethinkDB and GeoJSON):
r.db("strongloop").table("region").insert(
r.http("91231cd2.ngrok.io/data/geojson/MP14_REGION_WEB_PL_FLAT.json")("features")
.merge(function(zone) {
return {
zone: r.geojson(zone("geometry"))
}
}))
This approach gives me following error:
RqlRuntimeError: Invalid LinearRing. Are there antipodal or duplicate vertices? Is it self-intersecting? in: r.db("strongloop").table("region").insert(r.http("91231cd2.ngrok.io/data/geojson/MP14_REGION_WEB_PL_FLAT.json")("features").merge(function(var_63) { return {zone: r.geojson(var_63("geometry"))}; }))
I suspect it is because the geojson comes from flattened multipolygon (done using geojson.io Meta feature since RethinkDB does not support multipolygon) - but visually, the polygon is what I expected. I've also attempted to use r.polygon approach as following:
r.db("strongloop").table("region").insert(
r.http("91231cd2.ngrok.io/data/geojson/MP14_REGION_WEB_PL_FLAT.json")("features")
.merge(function(zone) {
return {
zone: r.polygon(zone("geometry")("coordinates"))
}
}))
but RethinkDB expects me to give array of points
RqlCompileError: Expected 3 or more arguments but found 1 in: r.db("strongloop").table("region").insert(r.http("91231cd2.ngrok.io/data/geojson/MP14_REGION_WEB_PL_FLAT.json")("features").merge(function(var_64) { return {zone: r.polygon(var_64("geometry")("coordinates"))}; }))
I could not figure out how to extract array of geometry coordinates before passing to r.polygon using code above.
How should I resolve this? Is there any better way?
Check URL
What happens if you do the http request by itself? I tried it and g0t a 404 on that resource. I would run that command first and make sure it works:
r.http("91231cd2.ngrok.io/data/geojson/MP14_REGION_WEB_PL_FLAT.json")
Try r.args
r.polygon expects 3 arguments, but you're passing it one. You might try using r.args to spread those arguments in the function (similar to Function.apply, if you're a JavaScript guy)
r.db("strongloop").table("region").insert(
r.http("91231cd2.ngrok.io/data/geojson/MP14_REGION_WEB_PL_FLAT.json") ("features")
.merge(function(zone) {
return {
zone: r.polygon(r.args(zone("geometry")("coordinates")))
}
}))
Invalid Polygons
It seems that one of your polygons might be invalid. If you use the input from the other answer you posted and you use it the following function, it will work:
r.expr(ARRAY_FROM_OTHER_ANSWER_WITH_POLYGONS).do(function (arr) {
// Remove middle element
return arr.slice(0, 2).add(arr.slice(3, 5))
// Map all elements to polygons
// Make sure you pass an array of LON/LATs into `r.polygon`
.map(function (row) {
return r.polygon(r.args(row('geometry')('coordinates')(0)));
});
})
Perhaps you can insert them one by one and catch the ones that failed.
The folowing query fails:
r.json(r.http('https://gist.githubusercontent.com/tekoadjaib/9e0f0729c050b69b283f/raw/6950765ed4a931b9b208e69a3c39b3114be5c7e3/map.geojson'))('features')
.map(function (row) {
return r.polygon(r.args(row('geometry')('coordinates')(0)))
})
While this one (slicing the first 17 elements) doesn't.
r.json(r.http('https://gist.githubusercontent.com/tekoadjaib/9e0f0729c050b69b283f/raw/6950765ed4a931b9b208e69a3c39b3114be5c7e3/map.geojson'))('features')
.slice(0, 17)
.map(function (row) {
return r.polygon(r.args(row('geometry')('coordinates')(0)))
})
Running this command on RethinkDB Data Explorer
r.http("6f892736.ngrok.io/data/geojson/MP14_REGION_WEB_PL_FLAT.json") ("features")
I received (removed some to fit SO limit)
[
{
"geometry": {
"coordinates": [
[
[
103.84874965353661,
1.363027350968694
],
[
103.84924291873233,
1.362752820720889
],
[
103.84935645049902,
1.362682483934137
],
[
103.84973091592526,
1.362406260504349
],
[
103.84992386166968,
1.362263929416379
],
[
103.85137091514449,
1.361102941278631
],
[
103.85194295836556,
1.360652909851773
],
[
103.8522672818684,
1.360326981650605
],
[
103.82714577966834,
1.241938910658531
],
[
103.82714429349235,
1.241945678019855
]
]
],
"type": "Polygon"
},
"properties": {
"FMEL_UPD_D": "2014/12/05",
"INC_CRC": "F6D4903B6C0B72F8",
"OBJECTID": 1,
"REGION_C": "CR",
"REGION_N": "CENTRAL REGION",
"SHAPE_Area": 136405631.404,
"SHAPE_Leng": 131065.464453,
"X_ADDR": 27836.5573,
"Y_ADDR": 31929.9186
},
"type": "Feature"
},
{
"geometry": {
"coordinates": [
[
[
103.82233409716747,
1.247288081083765
],
[
103.82235533213682,
1.247267117084279
],
[
103.82236522405806,
1.247257351790808
],
[
103.82239090120945,
1.24726873242952
],
[
103.82242101348092,
1.247282079176339
],
[
103.82244356466394,
1.247292075218428
],
[
103.8224842992999,
1.247310126516275
],
[
103.82229812450149,
1.247323592638841
],
[
103.82233409716747,
1.247288081083765
]
]
],
"type": "Polygon"
},
"properties": {
"FMEL_UPD_D": "2014/12/05",
"INC_CRC": "F6D4903B6C0B72F8",
"OBJECTID": 1,
"REGION_C": "CR",
"REGION_N": "CENTRAL REGION",
"SHAPE_Area": 136405631.404,
"SHAPE_Leng": 131065.464453,
"X_ADDR": 27836.5573,
"Y_ADDR": 31929.9186
},
"type": "Feature"
},
{
"geometry": {
"coordinates": [
[
[
103.81270485670082,
1.253738883481215
],
[
103.81270819925057,
1.253736038375202
],
[
103.81271747666578,
1.25372269002029
],
[
103.81272796270179,
1.253696608214719
],
[
103.81272550089241,
1.25367617858827
],
[
103.81271663253291,
1.253660777180855
],
[
103.81268489667742,
1.253637281524639
],
[
103.81271738240808,
1.253596580832204
],
[
103.81272993138482,
1.25358085854482
],
[
103.81277884770714,
1.253527980705921
],
[
103.81280844732579,
1.253491732178708
],
[
103.81284783649771,
1.253444824881476
],
[
103.81289710415396,
1.253390129269173
],
[
103.81268859863616,
1.253749463519217
],
[
103.81269418659909,
1.253747966839359
],
[
103.81269933160983,
1.253743587040128
],
[
103.81270485670082,
1.253738883481215
]
]
],
"type": "Polygon"
},
"properties": {
"FMEL_UPD_D": "2014/12/05",
"INC_CRC": "F6D4903B6C0B72F8",
"OBJECTID": 1,
"REGION_C": "CR",
"REGION_N": "CENTRAL REGION",
"SHAPE_Area": 136405631.404,
"SHAPE_Leng": 131065.464453,
"X_ADDR": 27836.5573,
"Y_ADDR": 31929.9186
},
"type": "Feature"
},
{
"geometry": {
"coordinates": [
[
[
103.81422064298785,
1.252570070111331
],
[
103.81420878069888,
1.252558437176131
],
[
103.8142083125649,
1.252558523991746
],
[
103.81420773751474,
1.252557413427196
],
[
103.81419024508641,
1.252540259301697
],
[
103.81418525918728,
1.252535369363019
],
[
103.81417827319876,
1.252525659143691
],
[
103.81417483815903,
1.252520884975136
],
[
103.81417401960785,
1.25251974727783
],
[
103.8141688845694,
1.252512609990775
],
[
103.81416372167686,
1.252505434720186
],
[
103.81415922015667,
1.252490646509147
],
[
103.81415911592985,
1.252490302849641
],
[
103.81415883649417,
1.252489384917013
],
[
103.81415845013613,
1.252488116994314
],
[
103.8141580341274,
1.252486750495618
],
[
103.8141581823891,
1.252486131910979
],
[
103.81415836569447,
1.252485366819468
],
[
103.81415859033339,
1.252484429898899
],
[
103.81415863076748,
1.252484387394026
],
[
103.81415862268139,
1.252484294244369
],
[
103.81416084480966,
1.252475025422944
],
[
103.81416187994584,
1.25247070708728
],
[
103.81416579397985,
1.252464651487459
],
[
103.81417344413717,
1.25245281611786
],
[
103.81417638235824,
1.25244826989617
],
[
103.81418792868888,
1.252415206393471
],
[
103.81423209597757,
1.252398253489821
],
[
103.8142345678362,
1.252397304828964
],
[
103.81423924468973,
1.252395510602936
],
[
103.8142416716218,
1.252394579124685
],
[
103.81424197622378,
1.252394461559454
],
[
103.81424641316956,
1.252392758672508
],
[
103.81427168974326,
1.252383056828959
],
[
103.81429695645653,
1.252370091131469
],
[
103.81430622571014,
1.252365335143192
],
[
103.81430795807904,
1.252364492287584
],
[
103.81430790237042,
1.252364474199889
],
[
103.8143179156083,
1.252359335670564
],
[
103.81433202075975,
1.252352098139711
],
[
103.81434014977647,
1.252347926362841
],
[
103.81435231859189,
1.252341681810603
],
[
103.81435985727103,
1.252338114145249
],
[
103.81437420681739,
1.25233151509769
],
[
103.81439499523958,
1.252321955205564
],
[
103.81439606179633,
1.252321465047431
],
[
103.81439624419711,
1.252321532876141
],
[
103.81440192381508,
1.25231876917771
],
[
103.81441291824507,
1.252313712952395
],
[
103.81442976570837,
1.252305965378984
],
[
103.81444317808666,
1.252299726261537
],
[
103.81445277979405,
1.252295146626335
],
[
103.81447443170696,
1.252284820742596
],
[
103.8144961555022,
1.252274461397674
],
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