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Searching by an attribute

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Search by Attribute Search by Attribute

This denotes implementing an attribute of a set of records as a facet. For an example,  in a record which represents a book, you can define the AUTHOR field as a facet when you are persisting the event stream as shown below.

Click the Simulate option of the event stream to simulate sending events to the created event stream. 

For the attribute which you defined as a facet,   you need to send its values as a JSON string array  as shown in the example  below . 

You can use this facet to retrieve the records of the books which are written by a particular author using the Data Explorer as shown in the example below.

You can perform the above search in the Analytics REST API using the following request. For more information, see  Drilling Down Through Categories via REST API.

POST https://localhost:9443/analytics/drillDown
 
{
           "tableName": "BOOK_STORE",
            "categories": [
                {
                          "fieldName": "AUTHOR",
                            "path" : ["C.Dickens"]
                }
            ],
            "query" : "timestamp : [1243214324532 TO 4654365223]",
            "recordStart" : 0,
            "recordCount" : 100
}

Extracting sub categories  

Another use of facets is to extract the sub categories of a category. You can retrieve the immediate sub-categories of a given category (which are represented in a JSON array), using the relevant API. The API returns the immediate subcategories of the given category in the corresponding table.  

For an example,  in a record which represents a book, you can define the PUBLISHED_DATE field as a facet when you are persisting the event stream as shown below.

Click the Simulate option of the event stream to simulate sending events to the created even stream.   

Send its values as a JSON string array for the attribute which you defined as a facet as shown in the example below.   

For an example, if the above BOOK_STORE  table contains the below four records with the corresponding values for  PUBLISHED_DATE , the REST API returns the sub categories of [“1926”], which are “08”, “04”, and the sub categories of [“1926”, “08”], which are “09” and “10".

• Record 1 -  PUBLISHED_DATE   :[“1926”, “08”, “09”]
• Record 2 -  PUBLISHED_DATE  :[“1926”, “04”, “02”]
• Record 3 -  PUBLISHED_DATE  :[“1816”, “09”, “01”]
• Record 4 -  PUBLISHED_DATE  :[“1926”, “08”, “10”]

You can  retrieve  PUBLISHED_DATE  as a specific category and its sub categories using the Data Explorer as shown below.

You can perform the above search in the Analytics REST API using the following requests. For more information, see Drilling Down Through Categories via REST API.

POST https://localhost:9443/analytics/facets
{
        "tableName" : "BOOK_STORE",
        "fieldName" : "PUBLISHED_DATE",
        "categoryPath" : ["1926"],
        "query" : "timestamp : [1213343534535 TO 465464564644]"
}

POST https://localhost:9443/analytics/facets
{
        "tableName" : "BOOK_STORE",
        "fieldName" : "PUBLISHED_DATE",
        "categoryPath" : ["1926","08"],
        "query" : "timestamp : [1213343534535 TO 465464564644]"
}

Performing a drill down search

This denotes a hierarchical implementation of a collection of several categories of attributes within one attribute.  The values of a set of records, which you can use to classify the records can be indexed as facets. Those fields which are indexed as facets are used to implement faceted search and drill-down.

For an example,  in a record which represents a book, you can define the  PUBLISHED_DATE  field as a facet when you are  persisting the event stream  as shown below.

Click the  Simulate  option of the event stream to simulate sending events to the created even stream.  

For the attribute which you defined as a facet,   you need to send its values as a JSON string array  as shown in the example  below . 

You can use a facet to  filter the books by the published date as a specific category and published year/month/date as its sub categories using the Data Explorer as shown below.

You can perform the above search in the Analytics REST API using the following request. It will return the records which match the drill down search. For more information, see Retrieving Specific Records through a Drill Down Search via REST API.

POST https://localhost:9443/analytics/drillDown
 
{
           "tableName": "BOOK_STORE",
            "categories": [
                {
                          "fieldName": "PUBLISHED_DATE",
                            "path" : ["1866", "05", "03"]
                }
            ],
            "query" : "timestamp : [1243214324532 TO 4654365223]",
            "recordStart" : 0,
            "recordCount" : 100
}

Also you can perform the above search in the Analytics REST API using the following request. It will return the number of records which match the drill down search. For more information, see Retrieving the Number of Records Matching the Drill Down Criteria via REST API. 

POST https://localhost:9443/analytics/drillDownCount
 
{
           "tableName": "BOOK_STORE",
            "categories": [
                {
                          "fieldName": "PUBLISHED_DATE",
                            "path" : ["1866", "05", "03"]
                }
            ],
            "query" : "timestamp : [1243214324532 TO 4654365223]
 			"recordStart" : 0,
            "recordCount" : 100
}

Searching data within a value range

This  denotes using facets to filter data based on a value range of an attribute which is defined as a facet.

For an example, in a record which represents a book, you can define the  PRICE  field as a facet when you are  persisting the event stream  as shown below.

Click the  Simulate  option of the event stream to simulate sending events to the created even stream.  

You can perform the above search in the Analytics REST API using the following request. For more information, see Retrieving the Event Count of Range Facets.

POST https://localhost:9443/analytics/rangecount

{
        "tableName": "BOOK_STORE",
        "rangeField" : "PRICE",
        "ranges" : [
                {
                        "label" : "20USD - 30USD",
                        "from" : 20,
                        "to" : 30
                },
                {
                        "label" : "30USD - 40USD",
                        "from" : 30,
                        "to" : 40
                }
        ],
        "query" : "*:*"
}