I have two kinds of documents in couchDB with following json type:
1.
{
"_id": "4a91f3e8-616a-431d-8199-ace00055763d",
"_rev": "2-9105188217acd506251c98cd4566e788",
"Vehicle": {
"type": "STRING",
"name": "Vehicle",
"value": "12345"
},
"Start": {
"type": "DATE",
"name": "Start",
"value": "2014-09-10T11:19:00.000Z"
}
}
2.
{
"_id": "4a91f3e8-616a-431d-8199-ace00055763d",
"_rev": "2-9105188217acd506251c98cd4566e788",
"Equipment": {
"type": "STRING",
"name": "Equipment",
"value": "12345"
},
"Start": {
"type": "DATE",
"name": "Start",
"value": "2014-09-10T11:19:00.000Z"
}
}
I want to make one view which search all these documents whose doc.Vehicle.value=12345 OR doc.Equipment.value=12345.
How can I make this view that will return all these kind of documents.
Thanks in advance.
Just emit both (yes, map functions may emits multiple times different key-values for the same doc) values with your view:
function(doc){
if (doc.Equipment) {
emit(doc.Equipment.value, null)
}
if (doc.Vehicle) {
emit(doc.Vehicle.value, null)
}
}
And request them by the same key:
http://localhost:5984/db/_design/ddoc/_view/by_equip_value?key="12345"
See also the Guide to Views for more info about CouchDB views.
With Kxepals Version, you cannot query the type of results ("12345" can be either Vehicle, OR Equipment). you can only see the result when you use "include_docs=true" and search inside the doc, or make a second query with the id of the results.
If you want to see the type (or Query by type) you need to extend the View :
..
if(doc.Equipment) {
emit (doc.Equipment.value,doc.Equipment.name);
}
if(doc.Vehicle) {
emit(doc.Vehicle.value,doc.Vehicle.name);
}
Here, the name is the value of the result rows.
But you can also define the results in the query, if you put the name as a first query item:
if(doc.Equipment) {
emit([doc.Equipment.name,doc.Equipment.value],null);
}
if(doc.Vehicle) {
emit ([doc.Vehicle.name,doc.Vehicle.value],null);
}
Here, the
Your Query for Vehicles:
/viewname?startkey=["Vehicle"]&Endkey=["Vehicle",{}]
Equipment:
/viewname?startkey=["Equipment"]&endkey=["Equipment,{}]
Here, the name is the first Item of the result rows key array.
Maybe this will help : http://de.slideshare.net/okurow/couchdb-mapreduce-13321353
BTW: Better solution would be :
{
"_id": "4a91f3e8-616a-431d-8199-ace00055763d",
"_rev": "2-9105188217acd506251c98cd4566e788",
"type": "Vehicle",
"value":"12345",
"Start": {
"type": "DATE",
"name": "Start", // ? maybe also obsolete, because already inside "Start" Element
"value": "2014-09-10T11:19:00.000Z"
}
}
{
"_id": "4a91f3e8-616a-431d-8199-ace00055763d",
"_rev": "2-9105188217acd506251c98cd4566e788",
"type": "Equipment",
"value":"12345",
"Start": {
"type": "DATE",
"name": "Start", // ? maybe also obsolete, because already inside "Start" Element
"value": "2014-09-10T11:19:00.000Z"
}
}
in this case you can use only one emit:
emit([doc.type,doc.value],null)
Related
I'm creating a json schema to define necessary data with data types. There is some data need to be set into required filed. But didn't find how to do it in its document.
For this json schema:
{
"type": "object",
"required": [
"version",
"categories"
],
"properties": {
"version": {
"type": "string",
"minLength": 1,
"maxLength": 1
},
"categories": {
"type": "array",
"items": [
{
"title": {
"type": "string",
"minLength": 1
},
"body": {
"type": "string",
"minLength": 1
}
}
]
}
}
}
json like
{
"version":"1",
"categories":[
{
"title":"First",
"body":"Good"
},
{
"title":"Second",
"body":"Bad"
}
]
}
I want to set title to be required, too. It's in a sub array. How to set it in json schema?
There are a few things wrong with your schema. I'm going to assume you're using JSON Schema draft 2019-09.
First, you want items to be an object, not an array, as you want it to apply to every item in the array.
If "items" is a schema, validation succeeds if all elements in the
array successfully validate against that schema.
If "items" is an array of schemas, validation succeeds if each
element of the instance validates against the schema at the same
position, if any.
https://datatracker.ietf.org/doc/html/draft-handrews-json-schema-02#section-9.3.1.1
Second, if the value of items should be a schema, you need to treat it like a schema in its own right.
If we take the item from your items array as a schema, it doesn't actually do anything, and you need to nest it in a properties keyword...
{
"properties": {
"title": {
"type": "string",
"minLength": 1
},
"body": {
"type": "string",
"minLength": 1
}
}
}
Finally, now your items keyword value is a schema (subschema), you can add any keywords you can normally use, such as required, the same as you have done previously.
{
"required": [
"title"
],
"properties": {
...
}
}
I have a simple string "PART_NUMBER" value as a field in solr. I would like to add an additional field which places that value in a URL field. To do this, I created a new field type, field, and copy field
"add-field-type": {
"name": "endpoint_url",
"class": "solr.TextField",
"positionIncrementGap": "100",
"analyzer": {
"tokenizer": {
"class": "solr.KeywordTokenizerFactory"
},
"filters": [
{
"class": "solr.PatternReplaceFilterFactory",
"pattern": "([\\s\\S]*)",
"replacement": "http://myurl/$1.jpg"
}
]
}
},
"add-field": {
"name": "URL",
"type": "endpoint_url",
"stored": true,
"indexed": true
},
"add-copy-field":{ "source":"PART_NUMBER", "dest":"URL" }
As some of you probably guessed, my query output looks like
{
"id": "1",
"PART_NUMBER": "ABCD1234",
"URL": "ABCD1234",
"_version_": 1645658574812086272
}
Because the endpoint_url fieldtype only modifies the index. Indeed, when doing my analysis, I get
http://myurl/ABCD1234.jpg
My question: Is there any way to apply a tokenizer or filter and feed it back in to the field value? I would prefer this output when returning the result:
{
"id": "1",
"PART_NUMBER": "ABCD1234",
"URL": "http://myurl/ABCD1234.jpg",
"_version_": 1645658574812086272
}
Is this possible to do in Solr?
Solution was posted here:
Custom Solr analyzers not being used during indexing
I need to use an Update Processors In order to change the field value before analysis. The process can be found here:
https://lucene.apache.org/solr/guide/8_1/update-request-processors.html
I'm using document references to import parent fields into a child document. While searches against the parent fields work, the parent fields themselves do not seem to be included in the search results, only child fields.
To use the example in the documentation, salesperson_name does not appear in the fields entry for id:test:ad::1 when using query=John, or indeed when retrieving id:test:ad::1 via GET directly.
Here's a simplified configuration for my document model:
search definitions
person.sd - the parent
search person {
document person {
field name type string {
indexing: summary | attribute
}
}
fieldset default {
fields: name
}
}
event.sd - the child
search event {
document event {
field code type string {
indexing: summary | attribute
}
field speaker type reference<person> {
indexing: summary | attribute
}
}
import field speaker.name as name {}
fieldset default {
fields: code
}
}
documents
p1 - person
{
"fields": {
"name": "p1"
}
}
e1 - event
{
"fields": {
"code": "e1",
"speaker": "id:n1:person::1"
}
}
query result
curl -s "http://localhost:8080/search/?yql=select%20*%20from%20sources%20*where%20name%20contains%20%22p1%22%3B" | python -m json.tool
This returns both e1 and p1, as you would expect, given that name is present in both. But the fields of e1 do not include the name.
{
"root": {
"children": [
{
"fields": {
"documentid": "id:n1:person::1",
"name": "p1",
"sddocname": "person"
},
"id": "id:n1:person::1",
"relevance": 0.0017429193899782135,
"source": "music"
},
{
"fields": {
"code": "e1",
"documentid": "id:n1:event::1",
"sddocname": "event",
"speaker": "id:n1:person::1"
},
"id": "id:n1:event::1",
"relevance": 0.0017429193899782135,
"source": "music"
}
],
...
"fields": {
"totalCount": 2
},
}
}
Currently you'll need to add the imported 'name' into the default summary by
import field speaker.name as name {}
document-summary default {
summary name type string{}
}
More about explicit document summaries in http://docs.vespa.ai/documentation/document-summaries.html
The result of your query will then return
"children": [
{
"fields": {
"documentid": "id:n1:person::1",
"name": "p1",
"sddocname": "person"
},
"id": "id:n1:person::1",
"relevance": 0.0017429193899782135,
"source": "stuff"
},
{
"fields": {
"code": "e1",
"documentid": "id:n1:event::1",
"name": "p1",
"sddocname": "event",
"speaker": "id:n1:person::1"
},
"id": "id:n1:event::1",
"relevance": 0.0017429193899782135,
"source": "stuff"
}
],
We'll improve the documentation on this. Thanks for the very detailed write-up.
Add "summary" to the indexing statement of the imported field in the parent document type.
E.g in the documentation example change the "name" field in the "salesperson" document type to say "indexing: attribute | summary".
Currently I have a hundreds of thousands of files like so:
{
"_id": "1234567890",
"type": "file",
"name": "Demo File",
"file_type": "application/pdf",
"size": "1400",
"timestamp": "1491421149",
"folder_id": "root"
}
Currently, I index all the names, and a client can search for files based on the name of the file. These files also have tags that need to be associated with the file but they also have specific labels.
An example would be:
{
"tags": [
{ "client": "john doe" },
{ "office": "virginia" },
{ "ssn": "1234" }
]
}
Is adding the tags array to my above file object the ideal solution if I want to be able to search thousands of files with a client of John Doe?
The only other solution I can think of is having something an object per tag and having an array of file ID's associated with each tag like so:
{
"_id": "11111111",
"type": "tag",
"label": "client",
"items": [
"1234567890",
"1222222222",
"1333333333"
]
}
With this being a LOT of objects I need to add tags to, I'd rather do it the most efficient way possible FIRST so I don't have to backtrack in the near future when I start running into issues.
Any guidance would be greatly appreciated.
Your original design, with a tags array, works well with Cloudant Search: https://console.ng.bluemix.net/docs/services/Cloudant/api/search.html#search.
With this approach you would define a single design document that will index any tag in the tags array. You do not have to create different views for different tags and you can use the Lucene syntax for queries: http://lucene.apache.org/core/4_3_0/queryparser/org/apache/lucene/queryparser/classic/package-summary.html#Overview.
So, using your example, if you have a document that looks like this with tags:
{
"_id": "1234567890",
"type": "file",
"name": "Demo File",
"file_type": "application/pdf",
"size": "1400",
"timestamp": "1491421149",
"folder_id": "root",
"tags": [
{ "client": "john doe" },
{ "office": "virginia" },
{ "ssn": "1234" }
]
}
You can create a design document that indexes each tag like so:
{
"_id": "_design/searchFiles",
"views": {},
"language": "javascript",
"indexes": {
"byTag": {
"analyzer": "standard",
"index": "function (doc) {\n if (doc.type === \"file\" && doc.tags) {\n for (var i=0; i<doc.tags.length; i++) {\n for (var name in doc.tags[i]) {\n index(name, doc.tags[i][name]);\n }\n }\n }\n}"
}
}
}
The function looks like this:
function (doc) {
if (doc.type === "file" && doc.tags) {
for (var i=0; i<doc.tags.length; i++) {
for (var name in doc.tags[i]) {
index(name, doc.tags[i][name]);
}
}
}
}
Then you would search like this:
https://your_cloudant_account.cloudant.com/your_db/_design/searchFiles/_search/byTag
?q=client:jack+OR+office:virginia
&include_docs=true
The solution, that comes into my mind would be using map reduce functions.
To do that, you would add the tags to your original document:
{
"_id": "1234567890",
"type": "file",
"name": "Demo File",
"file_type": "application/pdf",
"size": "1400",
"timestamp": "1491421149",
"folder_id": "root",
"client": "john",
...
}
Afterwards, you can create a design document, that looks like this:
{
"_id": "_design/query",
"views": {
"byClient": {
"map": "function(doc) { if(doc.client) { emit(doc.client, doc._id) }}"
}
}
}
After the view is processed, you can open it with
GET /YOURDB/_design/query/_view/byClient?key="john"
By adding the query parameter include_docs=true, the whole document will be returned, instead of the id.
You can also write your tags into an tags attribute, but you have to update the map function to match the new design.
More information about views can be found here:
http://docs.couchdb.org/en/2.0.0/api/ddoc/views.html
In my data, I have two fields that I want to use as an index together. They are sensorid (any string) and timestamp (yyyy-mm-dd hh:mm:ss).
So I made an index for these two using the Cloudant index generator. This was created successfully and it appears as a design document.
{
"index": {
"fields": [
{
"name": "sensorid",
"type": "string"
},
{
"name": "timestamp",
"type": "string"
}
]
},
"type": "text"
}
However, when I try to make the following query to find all documents with a timestamp newer than some value, I am told there is no index available for the selector:
{
"selector": {
"timestamp": {
"$gt": "2015-10-13 16:00:00"
}
},
"fields": [
"_id",
"_rev"
],
"sort": [
{
"_id": "asc"
}
]
}
What have I done wrong?
It seems to me like cloudant query only allows sorting on fields that are part of the selector.
Therefore your selector should include the _id field and look like:
"selector":{
"_id":{
"$gt":0
},
"timestamp":{
"$gt":"2015-10-13 16:00:00"
}
}
I hope this works for you!