- Composite SQL Queries
- User-Defined Functions
- JavaScript Integration
- Linq to SQL Translation
- DocumentDB SQL - Built-in Function
- DocumentDB SQL - Parameterized
- DocumentDB - Scalar Expressions
- DocumentDB SQL - Array Creation
- DocumentDB SQL - Aliasing
- DocumentDB SQL - Joins
- DocumentDB SQL - Iteration
- DocumentDB SQL - Order By Clause
- DocumentDB SQL - Value Keyword
- DocumentDB SQL - In Keyword
- DocumentDB - Between Keyword
- DocumentDB SQL - Operators
- DocumentDB SQL - Where Clause
- DocumentDB SQL - From Clause
- DocumentDB SQL - Select Clause
- DocumentDB SQL - Overview
- DocumentDB SQL - Home
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- Questions and Answers
- UPSC IAS Exams Notes
DocumentDB SQL - Where Clause
In this chapter, we will cover the WHERE clause, which is also optional pke FROM clause. It is used to specify a condition while fetching the data in the form of JSON documents provided by the source. Any JSON document must evaluate the specified conditions to be "true" to be considered for the result. If the given condition is satisfied, only then it returns specific data in the form of JSON document(s). We can use WHERE clause to filter the records and fetch only necessary records.
We will consider the same three documents in this example. Following is the AndersenFamily document.
{ "id": "AndersenFamily", "lastName": "Andersen", "parents": [ { "firstName": "Thomas", "relationship": "father" }, { "firstName": "Mary Kay", "relationship": "mother" } ], "children": [ { "firstName": "Henriette Thaulow", "gender": "female", "grade": 5, "pets": [ { "givenName": "Fluffy", "type": "Rabbit" } ] } ], "location": { "state": "WA", "county": "King", "city": "Seattle" }, "isRegistered": true }
Following is the SmithFamily document.
{ "id": "SmithFamily", "parents": [ { "familyName": "Smith", "givenName": "James" }, { "familyName": "Curtis", "givenName": "Helen" } ], "children": [ { "givenName": "Michelle", "gender": "female", "grade": 1 }, { "givenName": "John", "gender": "male", "grade": 7, "pets": [ { "givenName": "Tweetie", "type": "Bird" } ] } ], "location": { "state": "NY", "county": "Queens", "city": "Forest Hills" }, "isRegistered": true }
Following is the WakefieldFamily document.
{ "id": "WakefieldFamily", "parents": [ { "familyName": "Wakefield", "givenName": "Robin" }, { "familyName": "Miller", "givenName": "Ben" } ], "children": [ { "familyName": "Merriam", "givenName": "Jesse", "gender": "female", "grade": 6, "pets": [ { "givenName": "Charpe Brown", "type": "Dog" }, { "givenName": "Tiger", "type": "Cat" }, { "givenName": "Princess", "type": "Cat" } ] }, { "familyName": "Miller", "givenName": "Lisa", "gender": "female", "grade": 3, "pets": [ { "givenName": "Jake", "type": "Snake" } ] } ], "location": { "state": "NY", "county": "Manhattan", "city": "NY" }, "isRegistered": false }
Let’s take a look at a simple example in which WHERE clause is used.
In this query, in WHERE clause, the (WHERE f.id = "WakefieldFamily") condition is specified.
SELECT * FROM f WHERE f.id = "WakefieldFamily"
When the above query is executed, it will return the complete JSON document for WakefieldFamily as shown in the following output.
[ { "id": "WakefieldFamily", "parents": [ { "familyName": "Wakefield", "givenName": "Robin" }, { "familyName": "Miller", "givenName": "Ben" } ], "children": [ { "familyName": "Merriam", "givenName": "Jesse", "gender": "female", "grade": 6, "pets": [ { "givenName": "Charpe Brown", "type": "Dog" }, { "givenName": "Tiger", "type": "Cat" }, { "givenName": "Princess", "type": "Cat" } ] }, { "familyName": "Miller", "givenName": "Lisa", "gender": "female", "grade": 3, "pets": [ { "givenName": "Jake", "type": "Snake" } ] } ], "location": { "state": "NY", "county": "Manhattan", "city": "NY" }, "isRegistered": false, "_rid": "Ic8LAJFujgECAAAAAAAAAA==", "_ts": 1450541623, "_self": "dbs/Ic8LAA==/colls/Ic8LAJFujgE=/docs/Ic8LAJFujgECAAAAAAAAAA==/", "_etag": ""00000500-0000-0000-0000-567582370000"", "_attachments": "attachments/" } ]Advertisements