CFCouchbase supports all of the new functionality available in Couchbase Server 4.x, including document locking, replica reads and N1QL / SQL querying support. We will look at several example applications and N1QL queries that you can start using today in your ColdFusion development.
10. METHOD HOUSEKEEPING
1.* METHODS 2.* METHODS
add insert
incr
decr
counter
delete remove
newQuery
n1qlQuery
viewQuery
deleteDesignDocument removeDesignDocument
set
upsert
replace
setMulti upsertMulti
setWithCAS replaceWithCAS
The query() method will still be implemented and is a
facade for both n1ql and view queries
12. N1QL- Non 1st Normal Form Query Language
- Familiar SQL like syntax
- MapReduce Views
- Steep Learning Curve
- Limited Capabilities
- N1QL requires Couchbase Server 4.0+
13. ARITHMETIC + - * / % -val
COLLECTION ANY EVERY ARRAY FIRST EXISTS IN WITHIN
COMPARISON
= == != <> > >= < <=
(NOT) BETWEEN (NOT) LIKE IS (NOT) NULL
IS (NOT) MISSING IS (NOT) VALUED
CONDITIONAL CASE expression WHEN value THEN expression
CONSTRUCTION
Array [ value, value, ... ]
Object { key:value, key:value, ... }
LOGICAL AND OR NOT
STRING ||
N1QL OPERATORS
http://developer.couchbase.com/
documentation/server/current/n1ql/n1ql-
language-reference/operators.html
18. SELECT DIFFERENCES
SELECT *
FROM users
USE KEYS "user_101"
SELECT *
[
{
"users": {
"email": "Judah66@gmail.com",
"first_name": "Albin",
"last_name": "Price",
"user_id": 101,
"username": "Eudora43"
}
}
]
RESULTS
SELECT users.*
FROM users
USE KEYS "user_101"
SELECT ENTITY.*
[
{
"email": "Judah66@gmail.com",
"first_name": "Albin",
"last_name": "Price",
"user_id": 101,
"username": "Eudora43"
}
]
RESULTS
Documents are projected as the bucket or alias
name
19. ?
QUERY BY VALUE
SELECT u.*
FROM users AS u
WHERE u.username = 'Eudora43'
QUERY BY USERNAME
[
{
"email": "Judah66@gmail.com",
"first_name": "Albin",
"last_name": "Price",
"user_id": 197,
"username": "Eudora43"
}
]
RESULTS
STANDARD SDK OPERATION
// perform view query
results = couchbase.query(
designDocumentName="user",
viewName="username",
options={
key: "eudora43"
}
);
// get the document by the id
// returned from the query
user = couchbase.get(results[1].id);
function (doc, meta) {
if( doc.username ){
emit(
doc.username.toLowerCase(),
null
);
}
}
VIEW MAP FUNCTION
These queries are different. The N1QL query
does not take case into consideration the
View does. N1QL string operators are case
sensitive, the N1QL query would need to use
the LOWER() function
This can be done without N1QL, however it
would require a MapReduce View
This query would require a secondary
index
22. RETURNING
INSERT INTO users (KEY, VALUE)
VALUES ("user_2343", {
"user_id": 2343,
"name": "John Smith",
"email": "john.smith@gmail.com"
})
RETURNING *
N1QL INSERT W/ RETURNING
// write the user document
couchbase.insert("user_2343", {
"user_id": 2343,
"name": "John Smith",
"email": "john.smith@gmail.com"
});
// get the user document
user = couchbase.get("user_2343");
STANDARD SDK OPERATION
[
{
"users": {
"email": "john.smith@gmail.com",
"name": "John Smith",
"user_id": 2343
}
}
]
RESULTS
23. UPDATE
// get the user document
user = couchbase.get("user_2343");
// change the email value
user.email = "elmariachi@gmail.com";
// update the entire document
couchbase.replace("user_2343", user);
// read the write to get just the
// updated email value
user = couchbase.get("user_2343");
email = user.email;
STANDARD SDK OPERATIONN1QL UPDATE
UPDATE users
USE KEYS "user_2343"
SET email =
"elmariachi@gmail.com"
RETURNING email
SDK replace() will error if the document does
not exist, N1QL won’t
[
{
"email": "elmariachi@gmail.com"
}
]
RESULTS
24. UPSERT
// write the user document
couchbase.upsert("user_2343", {
"user_id": 2343,
"name": "John Smith",
"email": "john.smith@gmail.com"
});
// get the user document
user = couchbase.get("user_2343");
UPSERT INTO users (KEY, VALUE)
VALUES ("user_2343", {
"user_id": 2343,
"name": "John Smith",
"email": "john.smith@gmail.com"
})
RETURNING META().id AS document_id
N1QL UPSERT STANDARD SDK OPERATION
[
{
"document_id": "user2343"
}
]
RESULTS
25. DELETE
DELETE
FROM users
USE KEYS "user_2343"
N1QL DELETE
// write the user document
couchbase.remove("user_2343");
STANDARD SDK OPERATION
{
"results": [],
"metrics": {
"elapsedTime": "21.591512ms",
"executionTime": "21.559566ms",
"resultCount": 0,
"resultSize": 0
}
}
RESULTS SDK remove() will error if the document does not
exist, N1QL won’t
27. VIEW VS. GSI INDEXES
GSI INDEXES VIEW INDEXES
Partitioning Model
• Part of Index Service
• Each GSI Must be Unique
• Can only be placed on one node
• Can respond without scatter-gather
• Auto-partitioned with Data Service
• Expensive scatter-gather operations
Scaling Model • Scales with Index Service • Scales with Data Service
Performance
• Singleton Lookups or Range Scans can
respond without scatter-gather
• Singleton Lookups or Range Scans can
respond without scatter-gather
Managed Cache
• Comes with Managed Cache that performs
better during Index Maintenance and Scans
• Depends on File System Cache
Storage Engine • ForestDB • Couchstore
High Availability
• Multiple indexes with identical definitions
across multiple nodes
• Built-in replicas with smart placement
28. INDEXES
http://developer.couchbase.com/
documentation/server/current/indexes/gsi-
for-n1ql.html
• "USE KEYS" statements do not
require GSI Indexes
• All other N1QL queries require
GSI Indexes
• PRIMARY Index contains all keys
• Ad hoc queries require a
PRIMARY Index
• Index Names must be unique
• USING GSI is the default
CREATE PRIMARY INDEX idx_users_primary
ON users
USING GSI
PRIMARY INDEX
CREATE INDEX idx_users_username
ON users( username )
USING GSI
SECONDARY INDEX
DROP PRIMARY INDEX ON idx_users_primary
ON users
USING GSI
DROP PRIMARY INDEX
DROP PRIMARY INDEX idx_users_primary
ON users
USING GSI
DROP SECONDARY INDEX
29. EXPLAIN
EXPLAIN
SELECT u.*
FROM users AS u
WHERE u.username = 'Eudora43'
QUERY BY USERNAME
[
{
"plan": {
"#operator": "Sequence",
"~children": [
{
"#operator": "IndexScan",
"index": "idx_users_username",
"index_id": "240a59c3f5ced906",
"keyspace": "social",
"namespace": "default",
...
],
"using": "gsi"
},
...
]
},
...
}
]
RESULTS
http://developer.couchbase.com/
documentation/server/current/n1ql/n1ql-
language-reference/explain.html
31. INDEXES
CREATE INDEX idx_users_username
ON users( username )
WHERE username IS NOT MISSING
USING GSI
FILTERED INDEX
CREATE INDEX idx_users_username
ON users( username )
WHERE doc_type = 'user'
USING GSI
FILTERED INDEX
• Definitions can be duplicated
• Indexes can be partitioned
• Randomly assigned to an Index
nodes in the cluster
32. INDEXES
CREATE INDEX idx_users_username
ON users( username )
WHERE username IS NOT MISSING
USING GSI
WITH { "defer_build": true }
DEFER THE INDEX BUILD
BUILD INDEX
ON users(
idx_users_username,
idx_users_email
)
USING GSI
BUILD AN INDEX
CREATE INDEX idx_users_username
ON users( username )
WHERE username IS NOT MISSING
USING GSI
WITH { "nodes": "node3:8091"}
ADD INDEX TO SPECIFIC NODE
• Index builds can be deferred
• Multiple Indexes can be built at a
time
• Indexes can be deployed to
specific nodes
• GSI Indexes are not rebalanced
33. INDEX LOAD BALANCING
CREATE INDEX idx_users_username_AtoM
ON users( username )
WHERE doc_type = 'user'
AND username BETWEEN 'A' AND 'N'
USING GSI
RANGE PARTITIONED INDEXES
CREATE INDEX idx_users_username_NtoZ
ON users( username )
WHERE doc_type = 'user'
AND username BETWEEN 'N' AND 'Z'
USING GSI
- A round robin algorithm is used to distribute index load
- If a node responsible for a index goes down, a PrimaryIndexScan would be
used, or the query would fail if there is no PRIMARY INDEX
CREATE INDEX idx_users_username_AtoM_node1
ON users( username )
WHERE doc_type = 'user'
AND username BETWEEN 'A' AND 'N'
USING GSI WITH { "nodes": "node1:8091"}
REDUNDANT / REPLICATED INDEXES
CREATE INDEX idx_users_username_NtoZ_node1
ON users( username )
WHERE doc_type = 'user'
AND username BETWEEN 'N' AND 'Z'
USING GSI WITH { "nodes": "node1:8091"}
CREATE INDEX idx_users_username_AtoM_node2
ON users( username )
WHERE doc_type = 'user'
AND username BETWEEN 'A' AND 'N'
USING GSI WITH { "nodes": "node2:8091"}
CREATE INDEX idx_users_username_NtoZ_node2
ON users( username )
WHERE doc_type = 'user'
AND username BETWEEN 'N' AND 'Z'
USING GSI WITH { "nodes": "node2:8091"}
35. MISSING ATTRIBUTES
SELECT u.user_id, u.email, u.name
FROM users AS u
USE KEYS "user_197"
QUERY
{
"email": "Judah66@gmail.com",
"first_name": "Albin",
"last_name": "Price",
"user_id": 197,
"username": "Eudora43"
}
SAMPLE DOCUMENT
[
{
"email": "Judah66@gmail.com"
"user_id": 197
}
]
RESULT
Requested attributes that are missing are not returned as
part of the response
36. MISSING ATTRIBUTES
SELECT u.user_id, u.email,
IFMISSING(
u.name,
u.first_name || ' ' || u.last_name
) AS name
FROM users AS u
USE KEYS "user_197"
QUERY
{
"email": "Judah66@gmail.com",
"first_name": "Albin",
"last_name": "Price",
"user_id": 197,
"username": "Eudora43"
}
SAMPLE DOCUMENT
[
{
"email": "Judah66@gmail.com",
"name": "Albin Price",
"user_id": 197
}
]
RESULT
37. SELECT airlines.airline_id,
airlines.airline_name,
IFNULL(
airlines.airline_iata,
airlines.airline_icao
) AS airline_code
FROM `flight-data` AS codes
USE KEYS 'airline_code_DL'
INNER JOIN `flight-data` AS airlines
ON KEYS 'airline_' || TOSTRING( codes.id )
LIMIT 1
QUERY
[
{
"airline_code": "DL",
"airline_id": 2009,
"airline_name": "Delta Air Lines"
}
]
RESULT
{
"_id": "airline_code_DL",
"code": "DL",
"code_type": "iata",
"designation": "airline",
"doc_type": "code",
"id": 2009
}
AIRLINE LOOKUP DOCUMENT
{
"_id": "airline_2009",
"active": true,
"airline_iata": "DL",
"airline_icao": "DAL",
"airline_id": 2009,
"airline_name": "Delta Air Lines",
"callsign": "DELTA",
"doc_type": "airline",
"iso_country": "US"
}
AIRLINE DOCUMENT
JOINS
39. SELECT airlines.airline_name,
IFNULL(
airlines.airline_iata,
airlines.airline_icao
) AS airline_code,
source_airports.airport_name,
source_airports.iso_country,
source_airports.iso_region,
IFNULL(
source_airports.airport_iata,
source_airports.airport_icao,
source_airports.airport_ident
) AS airport_code
FROM `flight-data` AS routes
/* get airline details */
INNER JOIN `flight-data` AS airline_codes
ON KEYS 'airline_code_' || routes.airline_code
INNER JOIN `flight-data` AS airlines
ON KEYS 'airline_' || TOSTRING( airline_codes.id )
/* get airport details */
INNER JOIN `flight-data` AS airport_codes
ON KEYS 'airport_code_' || routes.source_airport_code
INNER JOIN `flight-data` AS source_airports
ON KEYS 'airport_' || TOSTRING( airport_codes.id )
WHERE routes.destination_airport_code = 'MSP'
AND routes.source_airport_code IS NOT NULL
AND routes.doc_type = 'route'
AND routes.active = true
ORDER BY source_airports.airport_name ASC,
airlines.airline_name ASC
QUERY
[
{
"airline_code": "DL",
"airline_name": "Delta Air Lines",
"airport_code": "ABR",
"airport_name": "Aberdeen Regional Airport",
"iso_country": "US",
"iso_region": "US-SD"
},
{
"airline_code": "DL",
"airline_name": "Delta Air Lines",
"airport_code": "ABQ",
"airport_name": "Albuquerque International Sunport",
"iso_country": "US",
"iso_region": "US-NM"
},
{
"airline_code": "DL",
"airline_name": "Delta Air Lines",
"airport_code": "BWI",
"airport_name": "Baltimore Washington Intl",
"iso_country": "US",
"iso_region": "US-MD"
},
...
]
RESULT
MULTIPLE JOINS
40. ANY
ANY variable ( IN | WITHIN ) expression
[ , variable ( IN | WITHIN ) expression ]*
SATISFIES condition END
EVERY
EVERY variable ( IN | WITHIN ) expression
[ , variable ( IN | WITHIN ) expression ]*
SATISFIES condition END
ARRAY
ARRAY expression FOR variable ( IN | WITHIN ) expression
[ , variable ( IN | WITHIN ) expression ]* [ ( WHEN condition) ] END
FIRST
FIRST expression FOR variable ( IN | WITHIN )
expression [ , variable ( IN | WITHIN ) expression]*
[ ( WHEN condition) ] END
EXISTS EXISTS expression
IN expression [ NOT ] IN expression
WITHIN expression [NOT] WITHIN expression
COLLECTION OPERATORS
http://developer.couchbase.com/
documentation/server/current/n1ql/
n1ql-language-reference/
collectionops.html
41. ANY OPERATOR
SELECT u.name, u.children
FROM users AS u
WHERE u.doc_type = 'user'
AND ANY child IN u.children
SATISFIES child.age > 10
END
ORDER BY ARRAY_LENGTH(u.children) ASC
QUERY
[
{
"children": [
{
"age": 12,
"first_name": "Emelia",
"gender": "M"
}
],
"name": "Elyse Rempel"
},
{
"children": [
{
"age": 15,
"first_name": "Yvette",
"gender": "F"
},
{
"age": 8,
"first_name": "Rodolfo",
"gender": "M"
}
],
"name": "Reynold Mohr"
},
...
]
RESULT
42. EVERY OPERATOR
SELECT u.name, u.children
FROM users AS u
WHERE u.doc_type = 'user'
AND EVERY child IN u.children
SATISFIES child.age > 10
AND child.gender = 'M'
END
ORDER BY ARRAY_LENGTH(u.children) ASC
QUERY
[
{
"children": [
{
"age": 16,
"first_name": "Grant",
"gender": "M"
}
],
"name": "Joseph Stiedemann"
},
{
"children": [
{
"age": 11,
"first_name": "Ezekiel",
"gender": "M"
},
{
"age": 12,
"first_name": "Brooks",
"gender": "M"
}
],
"name": "Aiden Christiansen"
},
...
]
RESULT
43. ARRAY INDEXING
[
{
"chat_id": "61bf583b2cd0",
"created_on": "2016-05-29T13:31:29.759Z"
},
{
"chat_id": "d63a56047e08",
"created_on": "2016-05-29T10:07:18.824Z"
},
...
]
RESULT
SELECT chats.chat_id,
MILLIS_TO_STR(chats.created_on) AS
created_on
FROM social AS chats
WHERE ANY user_id IN chats.users
SATISFIES user_id = 100
END
AND chats.doc_type = 'chat'
ORDER BY chats.created_on DESC
QUERY
CREATE INDEX idx_chats_users ON social(
DISTINCT ARRAY user_id
FOR user_id IN users
WHEN user_id IS NOT NULL
END,
doc_type
)
WHERE doc_type = 'chat'
INDEX
{
"_id": "chat_4ff8dd056225",
"doc_type": "chat",
"chat_id": "4ff8dd056225",
"created_on": 1464518742983,
"users": [
861,
492
]
}
SAMPLE DOCUMENT
44. {
"_id": "user_764",
"doc_type": "user",
"user_id": 764,
"first_name": "Geovanny",
"last_name": "Parker",
"phones": [
{
"type": "Mobile",
"phone_number": "676.825.8926",
"extension": null
},
{
"type": "Mobile",
"phone_number": "792.877.3144",
"extension": "3644"
},
{
"type": "Home",
"phone_number": "(730) 490-6734",
"extension": null
}
]
}
SAMPLE DOCUMENT
SELECT u.phones
FROM users AS u
USE KEYS 'user_764'
QUERY
[
{
"phones": [
{
"type": "Mobile",
"phone_number": "676.825.8926",
"extension": null
},
{
"type": "Mobile",
"phone_number": "792.877.3144",
"extension": "3644"
},
{
"type": "Home",
"phone_number": "(730) 490-6734",
"extension": null
}
]
}
]
RESULT
UNNEST
This query will only provide a single result
with a nested "phones" attribute that is an
array
45. UNNEST
{
"_id": "user_764",
"doc_type": "user",
"user_id": 764,
"first_name": "Geovanny",
"last_name": "Parker",
"phones": [
{
"type": "Mobile",
"phone_number": "676.825.8926",
"extension": null
},
{
"type": "Mobile",
"phone_number": "792.877.3144",
"extension": "3644"
},
{
"type": "Home",
"phone_number": "(730) 490-6734",
"extension": null
}
]
}
SAMPLE DOCUMENT
SELECT phone_numbers.*
FROM users AS u
USE KEYS 'user_23'
UNNEST u.phones AS phone_numbers
QUERY
[
{
"type": "Mobile",
"phone_number": "676.825.8926",
"extension": null
},
{
"type": "Mobile",
"phone_number": "792.877.3144",
"extension": "3644"
},
{
"type": "Home",
"phone_number": "(730) 490-6734",
"extension": null
}
]
RESULT
UNNSET performs a JOIN on a
documents attribute that is an array
with its parent document
46. NEST
SELECT u.first_name, u.last_name,
user_phones
FROM users AS u
USE KEYS 'user_581'
INNER NEST users AS user_phones
ON KEYS 'user_' || TOSTRING( u.user_id ) || '_phones'
QUERY
[
{
"first_name": "Geovanny",
"last_name": "Parker",
"user_phones": [
{
"_id": "user_581_phones",
"doc_type": "user-phones",
"phones": [
{
"extension": null,
"phone_number": "872-201-8963",
"phone_type": "Mobile"
},
{
"extension": "9324",
"phone_number": "720.194.5604",
"phone_type": "Other"
}
],
"user_id": 581
}
]
}
]
RESULT
{
"_id": "user_581_phones",
"doc_type": "user-phones",
"user_id": 581,
"phones": [
{
"extension": null,
"phone_number": "872-201-8963",
"phone_type": "Mobile"
},
{
"extension": "9324",
"phone_number": "720.194.5604",
"phone_type": "Other"
}
]
}
{
"_id": "user_581",
"doc_type": "user",
"user_id": 581,
"first_name": "Geovanny",
"last_name": "Parker"
}
USER DOCUMENT
USER PHONES DOCUMENT
A NEST operation will take 0 or more
documents and nest them as a single entry in
the result
INNER NEST will omit records if the right side
is missing
LEFT NEST will return records whether or not
the right side was found or not
48. NEST
SELECT u.user_id, u.first_name, u.last_name,
ARRAY
{
"phone_number": phone.phone_number,
"phone_type": phone.phone_type,
"extension": phone.extension
}
FOR phone IN IFMISSING(phones, [])
END AS phones
FROM users AS u
USE KEYS 'user_581'
LEFT NEST users AS phones ON KEYS (
ARRAY phone.phone_id FOR phone IN (
SELECT 'phone_' || phone_id AS phone_id
FROM users AS phone_lookup
USE KEYS
'user_' || TOSTRING(u.user_id) || '_phones'
UNNEST phone_lookup.phones AS phone_id
) END
)
QUERY
{
"_id": "user_581_phones",
"doc_type": "user-phones",
"user_id": 581,
"phones": [
"886350f7-3f97-5405-b6d0-294ecf469f05",
"8ee1bd2e-7b88-5d2c-a211-05a61ac367f8"
]
}
{
"_id": "user_581",
"doc_type": "user",
"user_id": 581,
"first_name": "Geovanny",
"last_name": "Parker"
}
USER DOCUMENT
USER PHONES DOCUMENT
{
"_id": "phone_886350f7-3f97-5405-b6d0-294ecf469f05",
"doc_type": "phone",
"phone_id": "886350f7-3f97-5405-b6d0-294ecf469f05",
"user_id": 581,
"phone_type": "Other",
"phone_number": "872-201-8963",
"extension": null
}
USER PHONES DOCUMENT
generates the same exact results as the
previous slide
49. AGGREGATES
SELECT COUNT(*) AS total_users
FROM social AS users
WHERE users.doc_type = 'user'
QUERY
[
{
"total_users": 1000
}
]
RESULT
SELECT ARRAY_COUNT(users.children) AS children
FROM social AS users
USE KEYS 'user_132'
QUERY
[
{
"children": 3
}
]
RESULT
SELECT MIN(children.age) AS min_age,
MAX(children.age) AS max_age,
AVG(children.age) AS avg_age
FROM social AS users
UNNEST users.children AS children
WHERE users.doc_type = 'user'
QUERY
[
{
"avg_age": 8.94,
"max_age": 17,
"min_age": 1
}
]
RESULT
http://developer.couchbase.com/
documentation/server/current/n1ql/n1ql-
language-reference/aggregatefun.html
52. NAMED PARAMS
couchbase.n1qlQuery(
statement="
SELECT airport_id,
airport_name, airport_type,
municipality, geo, timezone,
airport_iata, airport_icao,
FROM `flight-data`
WHERE iso_country = $country
AND iso_region = $region
AND doc_type = $doc_type
ORDER BY airport_name ASC
LIMIT 2
",
parameters={
'country': "US",
'region': "US-VT",
'doc_type': "airport"
}
);
SDK QUERY RESULT
53. PREPARED STATEMENTS
couchbase.n1qlQuery("
PREPARE
SELECT COUNT(1) AS total_airports
FROM `flight-data`
WHERE iso_country = 'US'
AND iso_region IS NOT NULL
AND doc_type = 'airport'
");
PREPARE QUERY PREPARE RESULT
couchbase.n1qlQuery("
EXECUTE
'9e4e1d3d-f1c3-4292-81cb-824af1fae87e'
");
EXECUTE QUERY
EXECUTE RESULT
Prepared Statements are stored in memory
until a server restart
54. NAMED PREPARED STATEMENTS
couchbase.n1qlQuery("
PREPARE us_airports
FROM
SELECT COUNT(1) AS total_airports
FROM `flight-data`
WHERE iso_country = 'US'
AND iso_region IS NOT NULL
AND doc_type = 'airport'
");
PREPARE QUERY RESULT
couchbase.n1qlQuery("
EXECUTE 'us_airports'
");
EXECUTE QUERY RESULT
55. DOCUMENT LOCKING
user = couchbase.getAndLock("user_101");
PREPARE QUERY
RESULT
• Default lock time is 5 seconds
• Max lock time is 30 seconds
• Prevents retrieval while Locked
• Prevents updates while Locked
• An update requires CAS
56. UNLOCKING A DOCUMENT
// replace the document using CAS
couchbase.replaceWithCAS(
id="user_101",
value=doc,
cas=user.cas
);
REPLACING THE DOCUMENT W/ CAS
RESULT
// update the document
couchbase.upsert("user_101", doc);
// replace the document
couchbase.replace("user_101", doc);
WHILE LOCKED UPSERT AND REPLACE WILL FAIL
ERROR
// unlock the document, returns true or
// false if the unlock was successful
couchbase.unlock(
id="user_101",
cas=user.cas
);
USING UNLOCK
Documents will automatically unlock after the
"lock time" has been exceeded
57. REPLICA READS
try {
// retrieve and lock the document
result = couchbase.get("user_100");
} catch(any e){
// attempt to get the document from a replica
result = couchbase.getFromReplica("user_100");
}
// replica reads return an array for each
// configured replica in the bucket
if (isArray(result)) {
result = result[0];
}
GET DOCUMENT FROM REPLICA(S)
58. COUNTERS
// increment the user counter
next_id = couchbase.counter(
id="user_counter",
value=1,
defaultValue=0
);
couchbase.insert("user_" & next_id, {
"user_id": next_id,
"name": "John Smith",
"email": "john.smith@email.com"
});
INCREMENT VALUE
// decrement the tickets counter
available_tix = couchbase.counter(
id="tickets_counter",
value=-1,
defaultValue=1000
);
// if there are no more tickets
// available redirect the user
if (available_tix < 1) {
cflocation(url="sold-out.cfm",
addtoken=false);
}
...
DECREMENT VALUE
Counter operations are Atomic
63. ROADMAP
• FULL TEXT SEARCHING (COMING IN CB 4.5)
• SUBDOC SUPPORT
• REMOVAL OF DEPRECATED METHODS
• SDK ALIGNMENT
• REGULAR RELEASE CYCLE
• MORE EXAMPLES
