{"id":1636,"date":"2020-03-23T12:07:56","date_gmt":"2020-03-23T19:07:56","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/json-case-sensitive-insensitive-search-index-data\/"},"modified":"2020-03-23T12:07:56","modified_gmt":"2020-03-23T19:07:56","slug":"json-case-sensitive-insensitive-search-index-data","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/json-case-sensitive-insensitive-search-index-data\/","title":{"rendered":"JSON is Case Sensitive. You Don’t Have to Be."},"content":{"rendered":"\n
\n

A RoSe by any other case would smell as sweet. William Shakespeare<\/a><\/p>\n<\/blockquote>\n\n\n\n

You must have learned <\/span>capitalization rules<\/span><\/a> in your grammar school, but the real-world search is not so sensitive to capitalization. Charles de Gaulle uses lower case for the middle \u201cde\u201d, Tony La Russa uses upper case for \u201cLa\u201d – there may be etymological reasons for it, but it’s unlikely for your customer service agent to remember.\u00a0\u00a0 <\/span>Databases have a variety of sensitivities.\u00a0 SQL, by default, is case insensitive to identifiers and keywords, but case sensitive to data. <\/span>JSON is case sensitive to both field names and data.\u00a0 So is N1QL.\u00a0\u00a0JSON can have the following. N1QL will select-join-project each field and value as a distinct field and value.<\/p>\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]SELECT {“City”: “San Francisco”, “city”: “san francisco”, “citY”: “saN fanciscO”}<\/p>\n

[
\n {
\n “$1”: {
\n “City”: “San Francisco”,
\n “citY”: “saN fanciscO”,
\n “city”: “san francisco”
\n }
\n }
\n][\/crayon]<\/p>\n\n\n\n

In this article, we’ll discuss dealing with data case sensitivity<\/strong>. Your field references are still case sensitive<\/strong>. If you use the wrong case for the field name, N1QL assumes this is a missing field and assigns MISSING value to that field.<\/p>\n\n\n\n

Let’s consider a simple predicate in N1QL to lookup all permutations of cases.<\/p>\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]
\n[\/crayon]<\/p>\n\n\n\n

This requires seven different lookups into the index.\u00a0 “John” requires more index lookups and “Fitzerald” requires even more. <\/span>There is a standard way to do this. Simply create an index by lowering the case of the field and the literal.<\/span><\/p>\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE LOWER(name) = \u201cjoe\u201d[\/crayon]<\/p>\n\n\n\n

This lookup can be made faster by creating the index with the right expression.<\/span><\/p>\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]CREATE INDEX i1 ON customer(LOWER(name));[\/crayon]<\/p>\n\n\n\n

Ensure that your query is picking up the right index and pushes the predicate to the index scan. And that\u2019s the idea. Queries that have predicates pushed to the index scan run much faster than the queries that won\u2019t.\u00a0 This is true for predicates and true aggregate pushdown<\/a> as well.<\/span><\/p>\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]EXPLAIN SELECT * FROM `customer` WHERE LOWER(name) = “joe”;<\/p>\n

{
\n “#operator”: “IndexScan3”,
\n “index”: “i1”,
\n “index_id”: “c117bdf583c2e276”,
\n “index_projection”: {
\n “primary_key”: true
\n },
\n “keyspace”: “customer”,
\n “namespace”: “default”,
\n “spans”: [
\n {
\n “exact”: true,
\n “range”: [
\n {
\n “high”: “”joe””,
\n “inclusion”: 3,
\n “low”: “”joe””
\n }
\n ]
\n }
\n ],[\/crayon]<\/p>\n\n\n\n

Case insensitivity in a composite index scenario.<\/strong><\/h5>\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE LOWER(name) = \u201cjoe\u201d
\nAND zip = 94821
\nAND salary > 500
\nAND join_date <= \u201c2017-01-01\u201d
\nAND LOWER(county) LIKE \u201csan%\u201d[\/crayon]<\/p>\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]CREATE INDEX i2 ON customer(LOWER(name),
\n zip,
\n LOWER(county),
\n join_date,
\n salary)[\/crayon]<\/p>\n\n\n\n

Case insensitivity in Array functions.<\/strong><\/h5>\n\n\n\n

String functions<\/span><\/a> like SPLIT(), SUFFIXES(), many of the <\/span>array functions<\/span><\/a> and <\/span>object functions<\/span><\/a> do return arrays. So how do you use them in a case insensitive way?<\/span><\/p>\n\n\n\n

We follow the same principle as before.\u00a0 Create an expression to lower case the values first before you process them via these functions.\u00a0<\/span><\/p>\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]SELECT SPLIT(“Good Morning, Joe”) as splitresult;
\n “splitresult”: [
\n “Good”,
\n “Morning,”,
\n “Joe”
\n ]<\/p>\n

SELECT SPLIT(LOWER(\u201cGood Morning, Joe\u201d));
\n “splitresult”: [
\n “good”,
\n “morning,”,
\n “joe”
\n ]
\n[\/crayon]<\/p>\n\n\n\n

Now, what you really want is to filter based on a value within the string.<\/span><\/p>\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE\u00a0 LOWER(xyz) LIKE \u201c%good%\u201d;[\/crayon]<\/p>\n\n\n\n

This is probably the worst predicate in SQL — in terms of performance.<\/span><\/p>\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]SELECT * FROM customer
\nWHERE\u00a0 x IN SPLIT(LOWER(xyz)) SATISFIES x = \u201cgood\u201d END[\/crayon]<\/p>\n\n\n\n

Now, what index would you create for this?\u00a0 ADVISE<\/a> comes in handy.<\/span><\/p>\n\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]
\n[\/crayon]<\/p>\n0<\/p>\n\n\n\n

As usual, verify your explain.<\/p>\n\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]
\n[\/crayon]<\/p>\n1<\/p>\n\n\n\n

If you\u2019d like to UNNEST and have a simple WHERE clause, use this query. Always verify your explain to ensure the predicates are pushed to index scan.<\/span><\/p>\n\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]
\n[\/crayon]<\/p>\n2<\/p>\n\n\n\n

Using Tokens\u00a0<\/strong><\/h5>\n\n\n\n

TOKENS() function makes it simple to get the lower case by taking that option as an argument.\u00a0 See the article <\/span>More Than LIKE: Efficient JSON Searching With N1QL<\/span><\/a> for details and examples<\/span><\/p>\n\n\n\n

Complex expressions.<\/strong><\/h5>\n\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]
\n[\/crayon]<\/p>\n3<\/p>\n\n\n\n

How could we optimize this?\u00a0 Index Advisor to the rescue. Again.<\/span><\/p>\n\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]
\n[\/crayon]<\/p>\n4<\/p>\n\n\n\n

Explain to confirm the plan:<\/span><\/p>\n\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]
\n[\/crayon]<\/p>\n5<\/p>\n\n\n\n

Bringing in the Big Guns: Full-Text Search<\/strong><\/h4>\n\n\n\n

As you’ve realized, this is a text processing and querying problem. FTS can scan, store, search text in various ways.\u00a0 Case insensitive search is one of them. Let’s see the plan for a simple search query.<\/p>\n\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]
\n[\/crayon]<\/p>\n6<\/p>\n\n\n\n

This is NOT the plan you want\u2026This is using a primary scan!<\/span><\/p>\n\n\n\n

After creating the text index on the bucket customer, things are much better:<\/span><\/p>\n\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]
\n[\/crayon]<\/p>\n7<\/p>\n\n\n\n

The default standard analyzer lowers all the tokens and therefore you\u2019ll find all the \u201cjoe\u201ds : JOE, joe, Joe, JOe, etc.\u00a0 \u00a0You can define a custom analyzer and provide specific instruction to lowercase the tokens.\u00a0 Here’s an example.<\/span><\/p>\n\n\n\n

[crayon theme=”neon” font-size=”17″ line-height=”20″ lang=”mysql” decode=”true”]WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]
\n[\/crayon]<\/p>\n8<\/p>\n\n\n\n

Here’s how you add it in the UI.\u00a0 See fine blog 8 Ways to Customize Couchbase Full-Text Search Indexes<\/a> for details on various ways to customize the FTS index.\"\"<\/a><\/p>\n\n\n\n

\u00a0<\/p>\n\n\n\n

\u00a0<\/p>\n\n\n\n

\u00a0<\/p>\n\n\n\n

\u00a0<\/p>\n\n\n\n

\u00a0<\/p>\n\n\n\n

\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"

A RoSe by any other case would smell as sweet. William Shakespeare You must have learned capitalization rules in your grammar school, but the real-world search is not so sensitive to capitalization. Charles de Gaulle uses lower case for the middle \u201cde\u201d, Tony La Russa uses upper case for \u201cLa\u201d – there may be etymological […]<\/p>\n","protected":false},"author":55,"featured_media":18,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"ppma_author":[291],"class_list":["post-1636","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"\nIs JSON Case Sensitive or Not? | Upper + Lowercase Sensitivity<\/title>\n<meta name=\"description\" content=\"In this post, Couchbase demonstrates why JSON is case sensitive in certain fields and how to work with this sensitivity. Find helpful examples and more here.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/json-case-sensitive-insensitive-search-index-data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"JSON is Case Sensitive. You Don't Have to Be.\" \/>\n<meta property=\"og:description\" content=\"In this post, Couchbase demonstrates why JSON is case sensitive in certain fields and how to work with this sensitivity. Find helpful examples and more here.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.couchbase.com\/blog\/json-case-sensitive-insensitive-search-index-data\/\" \/>\n<meta property=\"og:site_name\" content=\"The Couchbase Blog\" \/>\n<meta property=\"article:published_time\" content=\"2020-03-23T19:07:56+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/5\/2026\/05\/couchbase-nosql-dbaas.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1800\" \/>\n\t<meta property=\"og:image:height\" content=\"630\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Keshav Murthy\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@rkeshavmurthy\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Keshav Murthy\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.couchbase.com\\\/blog\\\/json-case-sensitive-insensitive-search-index-data\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.couchbase.com\\\/blog\\\/json-case-sensitive-insensitive-search-index-data\\\/\"},\"author\":{\"name\":\"Keshav Murthy\",\"@id\":\"https:\\\/\\\/www.couchbase.com\\\/blog\\\/#\\\/schema\\\/person\\\/c261644262bf98e146372fe647682636\"},\"headline\":\"JSON is Case Sensitive. 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