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Question and Answer

Chris Saxon

Thanks for the question, Ranga Prasad.

Asked: April 10, 2017 - 12:17 pm UTC

Last updated: April 12, 2017 - 12:33 pm UTC

Version: 12.1.0.2.0

Viewed 10K+ times! This question is

You Asked

Hello Tom,

We are getting below JSON data from front end application, for forming SQL condition like

"(price < 10.25 OR (category = 2 OR category = 1) OR (name like '%test%' OR in_stock=0))".

How I can convert below JSON data into relational table data i.e Rows with parent child relation to apply hierarchical query's on data.

{
  "condition": "AND",
  "rules": [
    {
      "id": "price",
      "field": "price",
      "type": "double",
      "input": "number",
      "operator": "less",
      "value": "10.25"
    },
    {
      "condition": "OR",
      "rules": [
        {
          "id": "category",
          "field": "category",
          "type": "integer",
          "input": "select",
          "operator": "equal",
          "value": "2"
        },
        {
          "id": "category",
          "field": "category",
          "type": "integer",
          "input": "select",
          "operator": "equal",
          "value": "1"
        }
      ]
    },
    {
      "condition": "OR",
      "rules": [
        {
          "id": "name",
          "field": "name",
          "type": "string",
          "input": "text",
          "operator": "contains",
          "value": "test"
        },
        {
          "id": "in_stock",
          "field": "in_stock",
          "type": "integer",
          "input": "radio",
          "operator": "equal",
          "value": "0"
        }
      ]
    }
  ],
  "valid": true
}

Thanks in advance
S Ranga Prasad

and Chris said...

You can use json_table to convert a JSON document to relational data. For example:

create table t (
  jdoc varchar2(2000)
);

insert into t values ('{
  "condition": "AND",
  "rules": [
    {
      "id": "price",
      "field": "price",
      "type": "double",
      "input": "number",
      "operator": "less",
      "value": "10.25"
    },
    {
      "condition": "OR",
      "rules": [
        {
          "id": "category",
          "field": "category",
          "type": "integer",
          "input": "select",
          "operator": "equal",
          "value": "2"
        },
        {
          "id": "category",
          "field": "category",
          "type": "integer",
          "input": "select",
          "operator": "equal",
          "value": "1"
        }
      ]
    },
    {
      "condition": "OR",
      "rules": [
        {
          "id": "name",
          "field": "name",
          "type": "string",
          "input": "text",
          "operator": "contains",
          "value": "test"
        },
        {
          "id": "in_stock",
          "field": "in_stock",
          "type": "integer",
          "input": "radio",
          "operator": "equal",
          "value": "0"
        }
      ]
    }
  ],
  "valid": true
}');

select j.condition, j.valid, substr(j.rules, 1, 20) 
from   t, json_table(jdoc, '$'
   columns (
     condition varchar2(10) path '$.condition',
     rules     varchar2(1000) format json without wrapper path '$.rules',
     valid varchar2(10) path '$.valid'
   )
) j;

CONDITION  VALID  SUBSTR(J.RULES,1,20)  
AND        true   [{"id":"price","fiel


You have multiple levels of arrays. To extract all of these out, you need to make multiple calls to json_table. Note you need to use the /*+ no_merge */ hint to chain these or you'll get an "ORA-40556: unsupported chaining of JSON_TABLE" error. 

with vals as (
  select /*+ no_merge */j.condition, j.valid, j.rules
from   t, json_table(jdoc, '$'
   columns (
     condition varchar2(10) path '$.condition',
     rules     varchar2(1000) format json path '$.rules',
     valid varchar2(10) path '$.valid'
   )
) j
)
  select j.* from vals, json_table(rules, '$[*]'
    columns (
      id varchar2(20) path '$.id',
      field varchar2(20) path '$.field',
      type varchar2(20) path '$.type'
    )  
  ) j;

ID     FIELD  TYPE    
price  price  double


http://docs.oracle.com/database/121/SQLRF/functions092.htm

If you're lucky enough to be on 12.2, you could check out the JSON data guide. This allows you to expose sections of a JSON document as virtual columns in your table:

http://docs.oracle.com/database/122/ADJSN/json-dataguide.htm

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Comments

Why not use NESTED

Stew Ashton, April 11, 2017 - 10:12 pm UTC

Unlike XMLTABLE, you don't have to chain JSON_TABLE invocations to access nested objects or arrays.
select j.*
from t,
json_table(jdoc, '$'
  columns (
    condition varchar2(9) path '$.condition',
    valid varchar2(5) path '$.valid',
    nested path '$.rules[*]'
    columns (
      dad_num for ordinality,
      dad_condition varchar2(8) path '$.condition',
      dad_id varchar2(6) path '$.id',
      dad_field varchar2(10) path '$.field',
      dad_type varchar2(9) path '$.type',
      nested path '$.rules[*]'
      columns (
        son_num for ordinality,
        son_id varchar2(10) path '$.id',
        son_field varchar2(10) path '$.field',
        son_type varchar2(10) path '$.type'
      )  
    )  
  )
) j;

CONDITION VALID    DAD_NUM DAD_COND DAD_ID DAD_FIELD  DAD_TYPE     SON_NUM SON_ID     SON_FIELD  SON_TYPE
--------- ----- ---------- -------- ------ ---------- --------- ---------- ---------- ---------- --------
AND       true           1          price  price      double                                               
AND       true           2 OR                                            1 category   category   integer
AND       true           2 OR                                            2 category   category   integer
AND       true           3 OR                                            1 name       name       string
AND       true           3 OR                                            2 in_stock   in_stock   integer

If there is unlimited recursion...

Stew Ashton, April 12, 2017 - 12:12 pm UTC

If there is no way of knowing how deep the recursion will be, then XML would be easier because Oracle supports the XQUERY language. For JSON, I tried using recursive subquery factoring:
with q1(dad, son, dad_cond, CONDITION, VALID, RULES, ID, FIELD, TYPE, INPUT, OPERATOR, VALUE) as (
  select null, lvl, null, CONDITION, VALID, RULES, ID, FIELD, TYPE, INPUT, OPERATOR, VALUE
  from t,
  json_table(jdoc, '$'
    columns (
      condition varchar2(10) path '$.condition',
      valid     varchar2(10) path '$.valid',
      nested path '$.rules[*]'
      columns (
        lvl for ordinality,
        rules varchar2(4000) format json without wrapper path '$',
        id        varchar2(10) path '$.id',
        field     varchar2(10) path '$.field',
        type      varchar2(10) path '$.type',
        input     varchar2(10) path '$.input',
        operator  varchar2(10) path '$.operator',
        value     varchar2(10) path '$.value'
      )
    )
  ) n
  union all
  select o.son, n.lvl, o.CONDITION, n.CONDITION, o.VALID, n.RULES, n.ID, n.FIELD, n.TYPE, n.INPUT, n.OPERATOR, n.VALUE
  from q1 o, 
  json_table(rules, '$'
    columns (
      condition varchar2(10) path '$.condition',
      nested path '$.rules[*]'
      columns (
        lvl for ordinality,
        rules varchar2(4000) format json without wrapper path '$',
        id        varchar2(10) path '$.id',
        field     varchar2(10) path '$.field',
        type      varchar2(10) path '$.type',
        input     varchar2(10) path '$.input',
        operator  varchar2(10) path '$.operator',
        value     varchar2(10) path '$.value'
      )
    )
  ) n
  where o.rules is not null and o.id is null
) search depth first by valid set order1
select
  start_paren || field ||' '|| operator ||' '|| value ||' '|| end_paren
  as txt
from (
  select order1, dad, son, CONDITION, VALID, ID, FIELD, TYPE, INPUT, OPERATOR, VALUE,
    case when son = 1 and dad is not null then '( ' end start_paren,
    case when order1 = max(order1) over() and dad is null then null
      when order1 = max(order1) over() then ')'
      when son = max(son) over(partition by dad) then ') ' || dad_cond
      else condition
    end end_paren
  from q1
)
where id is not null
order by order1;

TXT
-----------------------
price less 10.25 AND
( category equal 2 OR
category equal 1 ) AND
( name contains test OR
in_stock equal 0 )

Do a LISTAGG to get everything on the same line.
Chris Saxon
April 12, 2017 - 12:33 pm UTC

Nice work Stew.
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