Knowledge Base

Using apoc.load.jsonParams to load data from Zendesk into Neo4j to learn about article subscribers

The following document describes how to utilize the Zendesk API to load data from Zendesk into Neo4j, specifically data about users who have chosen to subscribe/follow Knowledge Base section(s). This document attempts to solve the issue described by the following questions from Zendesk Question & Answers. Although the Zendesk UI allows users to subscribe/follow a Knowledge Section it does not provide an equivalent UI for a Zendesk Administrator to see what users are subscribed to each section.

The Cypher below, will create supporting indexes and then iterate overr every section, request all the user_ids with said section, create the relationship between the user_id and section and then populate the user_id with more identifying details.

create index on :Section(id);
create index on :User(id);
create index on :Organization(id);

// get all sections
CALL apoc.load.jsonParams("",{Authorization:"Basic base64Encoded_username:password"},null)
  yield value as sectionvalue
  with sectionvalue
  unwind sectionvalue.sections as section_item
    Merge (n:Section {,, created_at:section_item.created_at, updated_at:section_item.updated_at,url:section_item.html_url})
    with as secid
    // foreach section then find the subscribers
    CALL apoc.load.jsonParams(""+secid+"/subscriptions.json?per_page=200",{Authorization:"Basic base64Encoded_username:password"},null)
       yield value as subscribervalue
       with subscribervalue, secid
       unwind subscribervalue.subscriptions as subscription_item
            // create the relationship from the User to the Secction through the :Follows relationship
            match (s:Section {id:secid}) with s,subscription_item
            merge (n:User {id: subscription_item.user_id})
            merge (n)-[:Follows {subscribed_on: subscription_item.created_at}]->(s)
            with subscription_item.user_id as s_userid
            CALL apoc.load.jsonParams(""+s_userid+".json",{Authorization:"Basic base64Encoded_username:password"},null)
                 yield value as userRecord
               with userRecord, s_userid
               unwind userRecord.user as uid
               match (n:User {id:s_userid})

match (n:User) where exists(n.organization_id)
      with n,n.organization_id as organization_id
      CALL apoc.load.jsonParams(""+organization_id+".json",{Authorization:"Basic base64Encoded_username:password"},null)
      yield value as orgRecord
      unwind orgRecord.organization as orgid
      with n,orgid
      merge (o:Organization {id:, name:, created_at: orgid.created_at})
      merge (n)-[:IS_MEMBER_OF_ORG]->(o);

and to load 140 nodes (81 Users, 7 Sections, 52 Organizations) and associated relationships took 54 seconds.

In the above Cypher code, you will need to replace all occurances of

`your_domain`  with the actual domain your Zendesk is hosted under
`base64Encoded_username:password` with the base64 encoding ( of a Zendesk
 Admin user and password who has Admin rights in Zendesk

Additionally, to use basic authentication, you must enable password access in the Zendesk Support admin interface at Admin > Channels > API.

Finally, per the Zendesk API, if you expect to have more than 100 results per API call you will need to consider Pagination.

Pagination By default, most list endpoints return a maximum of 100 records per page. You can change the number of records on a per-request basis by passing a per_page parameter in the request URL parameters. Example: per_page=50. However, you can’t exceed 100 records per page on most endpoints.

When the response exceeds the per-page maximum, you can paginate through the records by incrementing the page parameter. Example: page=3. List results include next_page and previous_page URLs in the response body for easier navigation:

Copying the above Cypher into a shell script file, for example build_zd.cql, will then allow for it to be run through cypher-shell by running

$ cat build_zd.cql | bin/cypher-shell

And the resultant graph model is thus defined as:


The entire graph thus appears as


To which we will see there are 4 Sections (i.e. green nodes/circles) which have no subscribers (i.e the 4 green nodes in the upper left corner). Three other sections have subscribers, though the Section on the right has the most subscribers (i.e blue nodes/circles) Additionally some subscribers/users have choosen to follow multiple sections.

Each Node is defined with the following properties




Useful Cypher statements to query the graph

  1. Find # of users subscribed by Section

    match     (n:Section)
               size (  (n)<-[:Follows]-() ) as subscribers
    order by   subscribers desc;
  2. Find users and associated organization, per section and when the user subscribed subscribed

    match (s:Section)<-[r:Follows]-(u:User)-[:IS_MEMBER_OF_ORG]->(o:Organization)
                r.subscribed_on as DateWhenSubscribed
    order by,