216 lines
6.2 KiB
Markdown
216 lines
6.2 KiB
Markdown
---
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layout: default
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title: JSON Support
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parent: SQL
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nav_order: 7
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---
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# JSON Support
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SQL plugin supports JSON by following [PartiQL](https://partiql.org/) specification, a SQL-compatible query language that lets you query semi-structured and nested data for any data format. The SQL plugin only supports a subset of the PartiQL specification.
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## Querying nested collection
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PartiQL extends SQL to allow you to query and unnest nested collections. In OpenSearch, this is very useful to query a JSON index with nested objects or fields.
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To follow along, use the `bulk` operation to index some sample data:
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```json
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POST employees_nested/_bulk?refresh
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{"index":{"_id":"1"}}
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{"id":3,"name":"Bob Smith","title":null,"projects":[{"name":"SQL Spectrum querying","started_year":1990},{"name":"SQL security","started_year":1999},{"name":"OpenSearch security","started_year":2015}]}
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{"index":{"_id":"2"}}
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{"id":4,"name":"Susan Smith","title":"Dev Mgr","projects":[]}
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{"index":{"_id":"3"}}
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{"id":6,"name":"Jane Smith","title":"Software Eng 2","projects":[{"name":"SQL security","started_year":1998},{"name":"Hello security","started_year":2015,"address":[{"city":"Dallas","state":"TX"}]}]}
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```
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### Example 1: Unnesting a nested collection
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This example finds the nested document (`projects`) with a field value (`name`) that satisfies the predicate (contains `security`). Because each parent document can have more than one nested documents, the nested document that matches is flattened. In other words, the final result is the cartesian product between the parent and nested documents.
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```sql
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SELECT e.name AS employeeName,
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p.name AS projectName
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FROM employees_nested AS e,
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e.projects AS p
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WHERE p.name LIKE '%security%'
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```
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Explain:
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```json
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{
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"from" : 0,
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"size" : 200,
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"query" : {
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"bool" : {
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"filter" : [
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{
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"bool" : {
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"must" : [
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{
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"nested" : {
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"query" : {
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"wildcard" : {
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"projects.name" : {
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"wildcard" : "*security*",
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"boost" : 1.0
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}
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}
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},
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"path" : "projects",
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"ignore_unmapped" : false,
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"score_mode" : "none",
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"boost" : 1.0,
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"inner_hits" : {
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"ignore_unmapped" : false,
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"from" : 0,
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"size" : 3,
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"version" : false,
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"seq_no_primary_term" : false,
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"explain" : false,
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"track_scores" : false,
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"_source" : {
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"includes" : [
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"projects.name"
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],
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"excludes" : [ ]
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}
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}
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}
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}
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],
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"adjust_pure_negative" : true,
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"boost" : 1.0
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}
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}
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],
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"adjust_pure_negative" : true,
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"boost" : 1.0
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}
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},
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"_source" : {
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"includes" : [
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"name"
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],
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"excludes" : [ ]
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}
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}
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```
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Result set:
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| employeeName | projectName
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:--- | :---
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Bob Smith | OpenSearch Security
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Bob Smith | SQL security
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Jane Smith | Hello security
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Jane Smith | SQL security
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### Example 2: Unnesting in existential subquery
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To unnest a nested collection in a subquery to check if it satisfies a condition:
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```sql
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SELECT e.name AS employeeName
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FROM employees_nested AS e
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WHERE EXISTS (
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SELECT *
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FROM e.projects AS p
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WHERE p.name LIKE '%security%'
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)
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```
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Explain:
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```json
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{
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"from" : 0,
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"size" : 200,
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"query" : {
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"bool" : {
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"filter" : [
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{
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"bool" : {
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"must" : [
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{
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"nested" : {
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"query" : {
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"bool" : {
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"must" : [
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{
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"bool" : {
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"must" : [
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{
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"bool" : {
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"must_not" : [
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{
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"bool" : {
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"must_not" : [
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{
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"exists" : {
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"field" : "projects",
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"boost" : 1.0
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}
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}
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],
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"adjust_pure_negative" : true,
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"boost" : 1.0
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}
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}
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],
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"adjust_pure_negative" : true,
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"boost" : 1.0
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}
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},
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{
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"wildcard" : {
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"projects.name" : {
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"wildcard" : "*security*",
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"boost" : 1.0
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}
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}
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}
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],
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"adjust_pure_negative" : true,
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"boost" : 1.0
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}
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}
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],
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"adjust_pure_negative" : true,
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"boost" : 1.0
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}
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},
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"path" : "projects",
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"ignore_unmapped" : false,
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"score_mode" : "none",
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"boost" : 1.0
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}
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}
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],
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"adjust_pure_negative" : true,
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"boost" : 1.0
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}
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}
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],
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"adjust_pure_negative" : true,
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"boost" : 1.0
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}
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},
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"_source" : {
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"includes" : [
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"name"
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],
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"excludes" : [ ]
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}
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}
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```
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Result set:
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| employeeName |
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:--- | :---
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Bob Smith |
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Jane Smith |
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