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[DOC-12282]: Feedback on Search Functions.
Add a link to the page explaining how to add a search index through the UI console. Integrated a reusable prerequisites section for setting up demonstration search indexes, ensuring consistent instructions across related documentation. Updated existing N1QL Search Function content to reference the new section and adjusted formatting for clarity.
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‎modules/n1ql/pages/n1ql-language-reference/searchfun.adoc

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Search functions enable you to use xref:search:search.adoc[Full Text Search (FTS)] queries directly within a {sqlpp} query.
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[float]
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=== Prerequisites
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[#prerequisities, float]
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== Prerequisites
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To use any of the search functions, the Search Service must be available on the cluster.
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It's recommended that you create a suitable Search index for the searches that you want to run.
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For more information, refer to xref:search:create-search-indexes.adoc[].
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[NOTE]
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--
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The examples in this page all assume that demonstration Search indexes have been created, as described in xref:fts:fts-demonstration-indexes.adoc[Demonstration Indexes].
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--
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include::partial$demonstration-index-prerequisite-section.adoc[]
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[float]
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=== Authorization
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== Authorization
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You do not need credentials for the Search Service to be able to use the search functions in a query.
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The role *Data Admin* must be assigned to those who intend to create indexes; and the role *Data Reader* to those who intend to perform searches.
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For information on creating users and assigning roles, see xref:learn:security/authorization-overview.adoc[Authorization].
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[float]
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=== When to Use Search Functions
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== When to Use Search Functions
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The search functions are useful when you need to combine a Full Text Search with the power of a {sqlpp} query; for example, combining joins and natural-language search in the same query.
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If the Full Text Search index being queried has its default mapping disabled and has a custom type mapping defined, the query needs to specify the type explicitly.
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The above query uses the demonstration index xref:fts:fts-demonstration-indexes.adoc#travel-sample-index-hotel-description[travel-sample-index-hotel-description], which has the custom type mapping "hotel".
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The above query uses the xref:prerequisities[demonstration index], which has the custom type mapping "hotel".
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For more information about defining custom type mappings within a Search index, refer to xref:search:create-type-mapping.adoc[Create a Type Mapping].
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Note that for {sqlpp} queries, only Search indexes with one type mapping are searchable.

‎modules/n1ql/partials/demonstration-index-prerequisite-section.adoc

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To run the examples on this page, you will need to create three indexes.
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To create the indexes, you can use:
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* The index editor built into the web console.
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* The REST API
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* The command line utility.
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For this exercise, the easiest way is to use the web console to import the index definitions below.
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If you need more information on creating search indexes using Couchbase Web UI, see xref:search:create-search-index-ui.adoc[]
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[tabs]
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====
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travel-sample-index-unstored::
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--
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[source,json]
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----
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{
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"name": "travel-sample-index-unstored",
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"type": "fulltext-index",
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"params": {
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"doc_config": {
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"docid_prefix_delim": "",
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"docid_regexp": "",
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"mode": "type_field",
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"type_field": "type"
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},
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"mapping": {
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"analysis": {
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"analyzers": {
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"singleAnalyzer": {
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"tokenizer": "single",
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"type": "custom"
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}
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}
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},
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"default_analyzer": "standard",
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"default_datetime_parser": "dateTimeOptional",
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"default_field": "_all",
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"default_mapping": {
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"dynamic": true,
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"enabled": true
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},
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"default_type": "_default",
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"docvalues_dynamic": false,
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"index_dynamic": true,
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"store_dynamic": false,
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"type_field": "_type"
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},
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"store": {
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"indexType": "scorch",
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"segmentVersion": 15
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}
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},
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"sourceType": "gocbcore",
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"sourceName": "travel-sample",
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"sourceUUID": "94387e8a4cefe4abeb51d92e28a696c6",
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"sourceParams": {},
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"planParams": {
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"maxPartitionsPerPIndex": 1024,
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"indexPartitions": 1,
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"numReplicas": 0
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},
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"uuid": "5e26bbd6c2c87069"
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}
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----
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--
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travel-sample-index-stored::
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--
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[source,json]
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----
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{
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"name": "travel-sample-index-stored",
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"type": "fulltext-index",
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"params": {
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"doc_config": {
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"docid_prefix_delim": "",
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"docid_regexp": "",
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"mode": "type_field",
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"type_field": "type"
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},
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"mapping": {
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"analysis": {
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"analyzers": {
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"letterAnalyzer": {
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"tokenizer": "letter",
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"type": "custom"
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}
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}
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},
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"default_analyzer": "standard",
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"default_datetime_parser": "dateTimeOptional",
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"default_field": "_all",
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"default_mapping": {
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"dynamic": true,
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"enabled": true
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},
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"default_type": "_default",
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"docvalues_dynamic": false,
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"index_dynamic": true,
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"store_dynamic": true,
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"type_field": "_type"
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},
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"store": {
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"indexType": "scorch",
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"segmentVersion": 15
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}
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},
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"sourceType": "gocbcore",
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"sourceName": "travel-sample",
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"sourceUUID": "94387e8a4cefe4abeb51d92e28a696c6",
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"sourceParams": {},
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"planParams": {
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"maxPartitionsPerPIndex": 1024,
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"indexPartitions": 1,
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"numReplicas": 0
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},
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"uuid": "16d6602d3193b526"
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}
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----
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--
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geoIndex::
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+
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--
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[source,json]
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----
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{
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"name": "geoIndex",
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"type": "fulltext-index",
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"params": {
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"doc_config": {
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"docid_prefix_delim": "",
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"docid_regexp": "",
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"mode": "type_field",
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"type_field": "type"
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},
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"mapping": {
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"default_analyzer": "standard",
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"default_datetime_parser": "dateTimeOptional",
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"default_field": "_all",
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"default_mapping": {
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"dynamic": true,
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"enabled": true,
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"properties": {
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"geo": {
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"enabled": true,
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"dynamic": false,
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"fields": [
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{
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"include_in_all": true,
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"index": true,
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"name": "geo",
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"store": true,
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"type": "geopoint"
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}
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]
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}
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}
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},
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"default_type": "_default",
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"docvalues_dynamic": false,
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"index_dynamic": true,
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"store_dynamic": false,
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"type_field": "_type"
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},
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"store": {
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"indexType": "scorch",
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"segmentVersion": 15,
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"spatialPlugin": "s2"
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}
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},
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"sourceType": "gocbcore",
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"sourceName": "travel-sample",
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"sourceUUID": "94387e8a4cefe4abeb51d92e28a696c6",
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"sourceParams": {},
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"planParams": {
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"maxPartitionsPerPIndex": 1024,
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"indexPartitions": 1,
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"numReplicas": 0
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},
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"uuid": "445bceb9301d0d74"
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}
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----
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--
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====

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