I have set up a "checkbox group" with the five schedule states in our organization's workspace. I would like to query using the Lookback API with the selected schedule states as filters. Since the LBAPI is driven by ObjectIDs, I need to pass in the ID representations of the schedule states, rather than their names. Is there a quick way to get these IDs so I can relate them to the checkbox entries?
Lookback API will accept string-valued ScheduleStates as query arguments. Thus the following query:
{
find: {
_TypeHierarchy: "HierarchicalRequirement",
"ScheduleState": "In-Progress",
__At:"current"
}
}
Works correctly for me. If you want/need OIDs though, and add &fields=true to the end of your REST query URL, you'll notice the following information coming back:
GeneratedQuery: {
{ "fields" : true,
"find" : { "$and" : [ { "_ValidFrom" : { "$lte" : "2013-04-18T20:00:25.751Z" },
"_ValidTo" : { "$gt" : "2013-04-18T20:00:25.751Z" }
} ],
"ScheduleState" : { "$in" : [ 2890498684 ] },
"_TypeHierarchy" : { "$in" : [ -51038,
2890498773,
10487547445
] },
"_ValidFrom" : { "$lte" : "2013-04-18T20:00:25.751Z" }
},
"limit" : 10,
"skip" : 0
}
}
You'll notice the ScheduleState OID here:
"ScheduleState" : { "$in" : [ 2890498684 ] }
So you could run a couple of sample queries on different ScheduleStates and find their corresponding OIDs.
Related
I need to GET list of nodes that contains certain label.
I know how to do that by getting entire nodes list by using Jenkins REST API and then getting node by node also REST API and checking its labels - but its to many API calls.
I also can create some job that writing to some place nodes list by label as parameter - but its bad way as Jenkins job that triggered remotely have no return value and I cant know it finished and will need read results from some other place the job saved it there.
I need some way that by one API call I will get nodes list contains a given label.
You can run a single API call to <JENKINS_URL>/computer/api/json (or <JENKINS_URL>/computer/api/python for a python api) which return a list of all nodes and their properties.
One of the properties is the label - so just go over all nodes and extract the ones that contain your needed label.
Here is an example for the returned object:
{
"_class" : "hudson.model.ComputerSet",
"busyExecutors" : 0,
"computer" : [
{
"_class" : "hudson.model.Hudson$MasterComputer",
"actions" : [
],
"assignedLabels" : [
{
"name" : "built-in"
}
],
"description" : "the Jenkins controller's built-in node",
"displayName" : "Built-In Node",
"executors" : [
{
},
{
}
],
"icon" : "symbol-computer",
"iconClassName" : "symbol-computer",
"idle" : true,
"jnlpAgent" : false,
"launchSupported" : true,
"loadStatistics" : {
"_class" : "hudson.model.Label$1"
},
"manualLaunchAllowed" : true,
"monitorData" : {
"hudson.node_monitors.SwapSpaceMonitor" : {
"_class" : "hudson.node_monitors.SwapSpaceMonitor$MemoryUsage2",
"availablePhysicalMemory" : 6938730496,
"availableSwapSpace" : 6906019840,
"totalPhysicalMemory" : 16885276672,
"totalSwapSpace" : 21046026240
},
"hudson.node_monitors.TemporarySpaceMonitor" : {
"_class" : "hudson.node_monitors.DiskSpaceMonitorDescriptor$DiskSpace",
"timestamp" : 1653907906021,
"path" : "C:\\Windows\\Temp",
"size" : 426696622080
},
"hudson.node_monitors.DiskSpaceMonitor" : {
"_class" : "hudson.node_monitors.DiskSpaceMonitorDescriptor$DiskSpace",
"timestamp" : 1653907905929,
"path" : "C:\\ProgramData\\Jenkins\\.jenkins",
"size" : 426696622080
},
"hudson.node_monitors.ArchitectureMonitor" : "Windows 10 (amd64)",
"hudson.node_monitors.ResponseTimeMonitor" : {
"_class" : "hudson.node_monitors.ResponseTimeMonitor$Data",
"timestamp" : 1653907905941,
"average" : 0
},
"hudson.node_monitors.ClockMonitor" : {
"_class" : "hudson.util.ClockDifference",
"diff" : 0
}
},
"numExecutors" : 2,
"offline" : false,
"offlineCause" : null,
"offlineCauseReason" : "",
"oneOffExecutors" : [
],
"temporarilyOffline" : false
}
],
"displayName" : "Nodes",
"totalExecutors" : 2
}
You are interested in the assignedLabels object - notice that it can contain multiple labels.
I have a mongodb query: (Give me the settings where account='test')
db.collection_name.find({"account" : "test1"}, {settings : 1}).pretty();
where I get the following sample output:
{
"_id" : ObjectId("49830ede4bz08bc0b495f123"),
"settings" : {
"clusterData" : {
"us-south-1" : "cluster1",
"us-east-1" : "cluster2"
},
},
What I'm looking for now, is to give me the account where the clusterData has more than 1 key.
I'm only interested in listing those accounts with (2) or more keys.
I've tried this: (but this doesn't work)
db.collection_name.find({'settings.clusterData.1': {$exists: true}}, {account : 1}).pretty();
Is this possible to do with the current data structure? I don't have the option to redesign this schema.
Your clusterData field is not an array which is why you cannot just filter the number of elements it has. There is a way, though, to get what you want via the aggregation framework. Try this:
db.collection_name.aggregate({
$match: {
"account" : "test1"
}
}, {
$project: {
"settingsAsArraySize": { $size: { $objectToArray: "$settings.clusterData" } },
"settings.clusterData": 1
}
}, {
$match: {
"settingsAsArraySize": { $gt: 1 }
}
}, {
$project: {
"_id": 0,
"settings.clusterData": 1
}
}).pretty();
I have a mongodb query: (Give me settings where account='test')
db.collection_name.find({"account" : "test1"}, {settings : 1}).pretty();
where I get the following output:
{
"_id" : ObjectId("49830ede4bz08bc0b495f123"),
"settings" : {
"clusterData" : {
"us-south-1" : "cluster1",
"us-east-1" : "cluster2"
},
},
What I'm looking for now, is to give me the account where the clusterData has more than 1 element in its array.
I'm only interested in listing those accounts with (2) or more elements.
I've tried this:
db.collection_name.find({'settings.clusterData.1': {$exists: true}}, {account : 1}).pretty();
Its not returning any results. Is my query correct? Is there another way to do this?
The reason that it isn't working is that your clusterdata is an object, not an array. I would suggest changing your data to be an array of clusters with two properties like below, then it will work.
{
"_id" : ObjectId("49830ede4bz08bc0b495f123"),
"settings" : {
"clusterData" : [
{
name : "cluster1",
location : "us-south-1"
},
{
name : "cluster2",
location : "us-east-1"
}
]
}
}
I recently run an Elasticsearch filter request that is
{
"from" : 0,
"size" : 10,
"query" : {
"filtered" : {
"filter" : {
"bool" : {
"must" : {
"terms" : {
"a_id" : [ 257793, 257798, 257844 ]
}
}
}
}
}
},
"explain" : false,
"fields" : "a_id"
}
So that I can find all docs with a_id in 257793, 257798, 257844 and the results are 257844, 257798, 257793. So far so good.
Then I find that whatever the sequence of the term numbers are, the return docs are always in the same a_id order. That is, even I run
"terms" : {
"a_id" : [257798, 257844, 257793 ]
}
The result docs are in the order of 257844, 257798, 257793 as well.
So I am so curious about the mechanism behind the Elasticsearch filtering. Can anyone help me and give me a hint?
By default, ES returns in descending order of _score. You can provide the sort option, to say in which order and based on what you want the results to be returned. For e.g., for based on date field
{
"sort": { "date": { "order": "desc" }}
"query" : {
"term" : { "user" : "kimchy" }
}
}
You can get more information:
https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-sort.html
https://www.elastic.co/guide/en/elasticsearch/guide/current/_sorting.html
I am using elastic search 1.4.1 - 1.4.4. I'm trying to index a geo polygon shape (document) into my index and now when the shape is indexed i want to know if a geo coordinate lies within the boundaries of that particular indexed geo-polygon shape.
GET /city/_search
{
"query":{
"filtered" : {
"query" : {
"match_all" : {}
},
"filter" : {
"geo_polygon" : {
"location" : {
"points" : [
[72.776491, 19.259634],
[72.955705, 19.268060],
[72.945406, 19.189611],
[72.987291, 19.169507],
[72.963945, 19.069596],
[72.914506, 18.994300],
[72.873994, 19.007933],
[72.817689, 18.896882],
[72.816316, 18.941052],
[72.816316, 19.113720],
[72.816316, 19.113720],
[72.790224, 19.192205],
[72.776491, 19.259634]
]
}
}
}
}
}
}
With above geo polygon filter i'm able get all indexed geo-coordinates lies within described polygon but i also need to know if a non-indexed geo-coordinate lies with in this geo polygon or not. My doubt is that if that is possible in the elastic search 1.4.1.
Yes, Percolator can be used to solve this problem.
As in normal use case of Elasticsearch, we index our docs into elasticsearch and then we run queries on indexed data to retrieve matched/ required documents.
But percolators works in a different way of it.
In percolators you register your queries and then you percolate your documents through registered queries and gets back the queries which matches your documents.
After going through infinite number of google results and many of blogs i wasn't able to find any thing which could explain how i can use percolators to solve this problem.
So i'm explaining this with an example so that other people facing same problem can take a hint from my problem and the solution i found. I would like if someone can improve my answer or can share a better approach of doing it.
e.g:-
First of all we need to create an index.
PUT /city/
then, we need to add a mapping for user document which consist a user's
latitude-longitude for percolating against registered queries.
PUT /city/user/_mapping
{
"user" : {
"properties" : {
"location" : {
"type" : "geo_point"
}
}
}
}
Now, we can register our geo polygon queries as percolators with id as city name or any other identifier you want to.
PUT /city/.percolator/mumbai
{
"query":{
"filtered" : {
"query" : {
"match_all" : {}
},
"filter" : {
"geo_polygon" : {
"location" : {
"points" : [
[72.776491, 19.259634],
[72.955705, 19.268060],
[72.945406, 19.189611],
[72.987291, 19.169507],
[72.963945, 19.069596],
[72.914506, 18.994300],
[72.873994, 19.007933],
[72.817689, 18.896882],
[72.816316, 18.941052],
[72.816316, 19.113720],
[72.816316, 19.113720],
[72.790224, 19.192205],
[72.776491, 19.259634]
]
}
}
}
}
}
}
Let's register another geo polygon filter for another city
PUT /city/.percolator/delhi
{
"query":{
"filtered" : {
"query" : {
"match_all" : {}
},
"filter" : {
"geo_polygon" : {
"location" : {
"points" : [
[76.846998, 28.865160],
[77.274092, 28.841104],
[77.282331, 28.753252],
[77.482832, 28.596619],
[77.131269, 28.395064],
[76.846998, 28.865160]
]
}
}
}
}
}
}
Now we have registered 2 queries as percolators and we can make sure by making this API call.
GET /city/.percolator/_count
Now to know if a geo point exist with any of registered cities we can percolate a user document using below query.
GET /city/user/_percolate
{
"doc": {
"location" : {
"lat" : 19.088415,
"lon" : 72.871248
}
}
}
This will return : _id as "mumbai"
{
"took": 25,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"total": 1,
"matches": [
{
"_index": "city",
"_id": "mumbai"
}
]
}
trying another query with different lat-lon
GET /city/user/_percolate
{
"doc": {
"location" : {
"lat" : 28.539933,
"lon" : 77.331770
}
}
}
This will return : _id as "delhi"
{
"took": 25,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"total": 1,
"matches": [
{
"_index": "city",
"_id": "delhi"
}
]
}
Let's run another query with random lat-lon
GET /city/user/_percolate
{
"doc": {
"location" : {
"lat" : 18.539933,
"lon" : 45.331770
}
}
}
and this query will return no matched results.
{
"took": 5,
"_shards": {
"total": 5,
"successful": 5,
"failed": 0
},
"total": 0,
"matches": []
}