JSON Index

JSON index can be applied to JSON string columns to accelerate the value lookup and filtering for the column.
When to use JSON index
JSON string can be used to represent the array, map, nested field without forcing a fixed schema. It is very flexible, but the flexibility comes with a cost - filtering on JSON string column is very expensive.
Suppose we have some JSON records similar to the following sample record stored in the person column:
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{
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  "name": "adam",
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  "age": 30,
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  "country": "us",
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  "addresses":
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  [
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    {
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      "number" : 112,
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      "street" : "main st",
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      "country" : "us"
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    },
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    {
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      "number" : 2,
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      "street" : "second st",
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      "country" : "us"
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    },
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    {
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      "number" : 3,
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      "street" : "third st",
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      "country" : "ca"
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    }
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  ]
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}
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Without an index, in order to look up a key and filter records based on the value, we need to scan and reconstruct the JSON object from the JSON string for every record, look up the key and then compare the value.
For example, in order to find all persons whose name is "adam", the query will look like:
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SELECT ... FROM mytable WHERE JSON_EXTRACT_SCALAR(person, '$.name', 'STRING') = 'adam'
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JSON index is designed to accelerate the filtering on JSON string columns without scanning and reconstructing all the JSON objects.
Configure JSON index
To enable the JSON index, set the following config in the table config:
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{
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  "tableIndexConfig": {        
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    "jsonIndexColumns": [
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      "person",
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      ...
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    ],
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    ...
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  }
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}
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Note that JSON index can only be applied to STRING columns whose values are JSON strings.
How to use JSON index
JSON index can be used via the JSON_MATCH predicate: JSON_MATCH(<column>, '<filterExpression>'). For example, to find all persons whose name is "adam", the query will look like:
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SELECT ... FROM mytable WHERE JSON_MATCH(person, '"$.name"=''adam''')
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Note that the quotes within the filter expression need to be escaped.
In release 0.7.1, we use the old syntax for filterExpression: 'name=''adam'''
Supported filter expressions
Simple key lookup
Find all persons whose name is "adam":
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SELECT ... FROM mytable WHERE JSON_MATCH(person, '"$.name"=''adam''')
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In release 0.7.1, we use the old syntax for filterExpression: 'name=''adam'''
Chained key lookup
Find all persons who have an address (one of the addresses) with number 112:
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SELECT ... FROM mytable WHERE JSON_MATCH(person, '"$.addresses[*].number"=112')
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In release 0.7.1, we use the old syntax for filterExpression: 'addresses.number=112'
Nested filter expression
Find all persons whose name is "adam" and also have an address (one of the addresses) with number 112:
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SELECT ... FROM mytable WHERE JSON_MATCH(person, '"$.name"=''adam'' AND "$.addresses[*].number"=112')
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In release 0.7.1, we use the old syntax for filterExpression: 'name=''adam'' AND addresses.number=112'
Array access
Find all persons whose first address has number 112:
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SELECT ... FROM mytable WHERE JSON_MATCH(person, '"$.addresses[0].number"=112')
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In release 0.7.1, we use the old syntax for filterExpression: '"addresses[0].number"=112'
Existence check
Find all persons who have phone field within the JSON:
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SELECT ... FROM mytable WHERE JSON_MATCH(person, '"$.phone" IS NOT NULL')
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In release 0.7.1, we use the old syntax for filterExpression: 'phone IS NOT NULL'
Find all persons whose first address does not contain floor field within the JSON:
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SELECT ... FROM mytable WHERE JSON_MATCH(person, '"$.addresses[0].floor" IS NULL')
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In release 0.7.1, we use the old syntax for filterExpression: '"addresses[0].floor" IS NULL'
JSON context is maintained
The JSON context is maintained for object elements within an array, i.e. the filter won't cross match different objects in the array.
To find all persons who live on "main st" in "ca":
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SELECT ... FROM mytable WHERE JSON_MATCH(person, '"$.addresses[*].street"=''main st'' AND "$.addresses[*].country"=''ca''')
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This query won't match "adam" because none of his addresses matches both the street and the country.
If JSON context is not desired, use multiple separate JSON_MATCH predicates. E.g. to find all persons who have addresses on "main st" and have addressed in "ca" (doesn't have to be the same address):
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SELECT ... FROM mytable WHERE JSON_MATCH(person, '"$.addresses[*].street"=''main st''') AND JSON_MATCH(person, '"$.addresses[*].country"=''ca''')
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This query will match "adam" because one of his addressed matches the street and another one matches the country.
Note that the array index is maintained as a separate entry within the element, so in order to query different elements within an array, multiple JSON_MATCH predicates are required. E.g. to find all persons who have first address on "main st" and second address on "second st":
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SELECT ... FROM mytable WHERE JSON_MATCH(person, '"$.addresses[0].street"=''main st''') AND JSON_MATCH(person, '"$.addresses[1].street"=''second st''')
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Supported JSON values
Object
See examples above.
Array
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["item1", "item2", "item3"]
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To find the records with array element "item1" in "arrayCol":
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SELECT ... FROM mytable WHERE JSON_MATCH(arrayCol, '"$[*]"=''item1''')
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To find the records with second array element "item2" in "arrayCol":
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SELECT ... FROM mytable WHERE JSON_MATCH(arrayCol, '"$[1]"=''item2''')
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Value
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123
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1.23
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"Hello World"
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To find the records with value 123 in "valueCol":
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SELECT ... FROM mytable WHERE JSON_MATCH(valueCol, '"quot;=123')
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Null
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null
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To find the records with null in "nullableCol":
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SELECT ... FROM mytable WHERE JSON_MATCH(nullableCol, '"quot; IS NULL')
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In release 0.7.1, json string must be object (cannot be null, value or array); multi-dimensional array is not supported.
Limitations
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The key (left-hand side) of the filter expression must be the leaf level of the JSON object, e.g. "$.addresses[*]"='main st' won't work.