No sq ls-biggest-lie_sql-never-went-away_martin-esmann

NoSQL's biggest lie: SQL never went away!
Martin Esmann
Developer Advocate, Couchbase
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Let’s do something unspectacular
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©2014 Couchbase Inc.
A query
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SELECT * FROM `travel-sample`
WHERE type = ‘airline’
AND country = ‘United Kingdom’;

A query
4

That was JSON
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We put the SQL back into NoSQL
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But first, let’s take a step back
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NoSQL?
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Polyglot persistence is “…using multiple data
storage technologies, chosen based upon the
way data is being used by individual
applications. Why store binary images in
relational database, when there are better
storage systems?”
Martin Fowler and Pramod Sadalage

Types of NoSQL database
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By Schumi4ever (Own work) [CC BY-SA 3.0
(http://creativecommons.org/licenses/by-sa/3.0)], via Wikimedia Commons

Key value
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Email: martin@couchbase.comemail:email: {
“personal”: “martin.esmann@hotmail.com”,
“work”: “martin@couchbase.com”
}

London
matthew@couchbase.com
james@couchbase.com
laura@couchbase.com
tom@couchbase.com
david@couchbase.com
greg@couchbase.com
Document
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Developer Advocacy
james@couchbase.com
laura@couchbase.com
laurent@couchbase.com
martin@couchbase.com
matt@couchbase.com
nic@couchbase.com
will@couchbase.com
martin@couchbase.com:
{
"city": ”Copenhagen",
"glasses": false,
"team": "Developer Advocacy",
"music": ”Electronic!"
}

Document
14
London
james@couchbase.com
laura@couchbase.com
Developer Advocacy
james@couchbase.com
laura@couchbase.com
London and Developer Advocacy
james@couchbase.com
laura@couchbase.com

And the others
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There's always a trade-off
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• Offload from some other data store (i.e. caching)
• Computation offload
• Speed
• Scalability
• Availability
• Flexibility in what you store
• Query flexibility

Couchbase Server 4.0
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High availability
cache
Key-value
store
Document
database N1QL SQL-like query
for JSON

A user profile as JSON
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Querying the JSON profile
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• Look-up documents: i.e. manual secondary indexing (2i)
• Couchbase views: i.e. automated secondary indexing (2i)
• N1QL

Manual 2i
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Automatic 2i: views
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SELECT
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SELECT ...

SELECT
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SELECT 1 + 1;
{
"requestID": "3ccebac7-341a-4c31-a2c5-b46aaed54356",
"signature": {
"$1": "number"
},
"results": [
{ "$1": 2
}
],
"status": "success",
"metrics": {
"elapsedTime": "31.826219ms",
"executionTime": "29.800616ms",
"resultCount": 1,
"resultSize": 31
}
}

SELECT COUNT
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SELECT COUNT(*) FROM `default`
WHERE office = "London";
{
"requestID": "6e733000-ac83-44ba-95a7-9b012e9c553d",
"signature": {
"$1": "number"
},
"results": [
{
"$1": 6
}
],
"status": "success",
"metrics": {
"elapsedTime": "18.603124ms",
"executionTime": "18.327696ms",
"resultCount": 1,
"resultSize": 31
}
}

SELECT email FROM `default`
WHERE office = "London";
SELECT
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WHERE office = "London"
AND team = "Developer Advocacy";
SELECT
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WHERE office = "London"
AND team != "Developer Advocacy";
SELECT
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SELECT conferences[0].name
AS event_name FROM `default`;
ARRAY ELEMENTS
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SELECT DISTINCT
conferences[0].name
AS event_name FROM `default`;
DISTINCT ARRAY ELEMENTS
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SELECT DISTINCT
conferences[0].name
AS event_name FROM `default`
WHERE conferences
IS NOT MISSING;
REMOVE MISSING ITEMS
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SELECT email AS person,
conferences[0].name AS event
FROM `default`
WHERE ANY event in conferences
SATISFIES event.name =
"Droidcon Sweden" END;
WHO IS GOING TO DROIDCON SWEDEN?
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What's going on underneath?
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EXPLAIN SELECT email AS person,
conferences[0].name AS event
FROM `default`
WHERE ANY event in conferences
SATISFIES event.name =
"Droidcon Sweden" END;
EXPLAIN
39

Updating and deleting
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• DELETE: provide the key to delete the document
• INSERT: provide a key and some JSON to create a new document
• UPSERT: as INSERT but will overwrite existing docs
• UPDATE: change individual values inside existing docs

UPDATE
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DELETE
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A larger data-set: travel-sample
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TRAVEL SAMPLE DATA
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travel-sample
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CREATE PRIMARY INDEX
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CREATE PRIMARY INDEX
ON `travel-sample`
USING GSI;

SELECT
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WHERE type = "airline";

SELECT
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SELECT
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WHERE type = "airline"
AND country = "United States";

SELECT
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CREATE INDEX
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CREATE INDEX airline
ON `travel-sample`(type)
WHERE type = "airline"
USING GSI;

JOINs
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• Retrieve data from two documents in a single SELECT
• Join within a keyspace/bucket
• Join across keyspaces/buckets

A SIMPLE JOIN
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SELECT * FROM `travel-sample` r
JOIN `travel-sample` a
ON KEYS r.airlineid
WHERE r.sourceairport="LHR"
AND r.destinationairport = "SFO";

WHO FLIES LHR->SFO?
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SELECT DISTINCT a.name FROM
`travel-sample` r
ON KEYS r.airlineid
AND r.destinationairport = "SFO";

UNNEST
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• Breaks out nested JSON from the results

SOMETHING USEFUL
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SELECT a.name, s.flight, s.utc, r.sourceairport,
r.destinationairport, r.equipment
FROM `travel-sample` r
UNNEST r.schedule s
ON KEYS r.airlineid
AND r.destinationairport = "SFO"
AND s.day=1
ORDER BY s.utc;

N1QL and views
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N1QL Views
Ad-hoc querying Predictable queries
JSON in and JSON out Number crunching
Large growth clusters Multi-dimensional/geospatial
queries

Scaling out
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Horizontal scaling
Partitions a dataset onto one or more homogenous nodes
Each node runs the same mixed workloads
Re-partition dataset with additional hardware capacity

What is Multi-Dimensional Scalability?
MDS is the architecture that enables independent scaling of data, query, and
indexing workloads.
Multi-dimensional scaling
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Isolated Service for minimized interference
Independent “zones” for query, index, and data services
Minimize indexing and query overhead on core key-value
operations.

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Independent scalability for the best computational capacity
per service
Heavier indexing (index more fields):
scale up index service nodes.
More RAM for query processing:
scale up query service nodes.

Geospatial views
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• Experimental in 3.0, now GA in 4.0
• Performance and stability improvements
• GeoJSON output
• Bounding-box and range queries on
multiple dimensions

What else is in Couchbase Server 4.0?
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Other new things in Couchbase Server 4.0
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• ForestDB: GSIs are stored with a new storage engine
• Filtered XDCR: more efficient cross-data centre replication
• Security: LDAP, admin auditing

Developers?
SDK support for N1QL!
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.NET SDK: Connection
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// Option 1: Create Cluster and open bucket
var cluster = new Cluster(config);
var bucket = cluster.OpenBucket(bucketName);
// Option 2: ClusterHelper and open bucket (Singleton, thread safe bucket instance
ClusterHelper.Initialize(config);
var cluster = ClusterHelper.Get();
var bucket = ClusterHelper.GetBucket(bucketName);
// Close connection
cluster.CloseBucket(bucket);
cluster.Dispose();

.NET SDK: Client Configuration
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// Cluster Configuration
var config = new ClientConfiguration
{
Servers = new List<Uri> { new Uri("http://10.211.55.2:8091/pools"),},
UseSsl = false,
BucketConfigs = new Dictionary<string, BucketConfiguration>
{
{
"travel-sample",
new BucketConfiguration
{
BucketName = "travel-sample",
UseSsl = false,
Password = "",
PoolConfiguration = new PoolConfiguration
{
MaxSize = 10,
MinSize = 5
}
}
}
}
};

.NET SDK: Basic Operations
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// Create document (dynamic)
var doc = new Document<dynamic>
{
Id = "doc1",
Content = new
{
Id = "doc1",
Title = "My Document",
Type = "basic",
Pages = 3
}
};
// update or create document
var upsertResult = await bucket.UpsertAsync<dynamic>(doc);
// Get document
var getResult = bucket.GetDocument<dynamic>("key1");
// Delete document
var deleteResult = await bucket.RemoveAsync<dynamic>(doc);
// Check if doc/key exsists
var exsists = await bucket.ExistsAsync("key1");

.NET SDK: N1QL Query (raw)
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// Create Query Request. Raw API request
var query = QueryRequest.Create("SELECT COUNT(*) FROM `travel-sample` WHERE type = 'airline'");
// Execute Query.
var response = await bucket.QueryAsync<dynamic>(query);
// Convert result to string for easy console print out.
var result = JsonConvert.SerializeObject(response, Formatting.Indented);

.NET SDK: N1QL Query (Linq2Couchbase)
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// Lambda syntax
var result = ClusterHelper.GetBucket("beer-sample")
.Queryable<Beer>()
.Where(a => a.Type == "beer")
.Select(a => a)
.Join(
ClusterHelper.GetBucket("beer-sample")
.Queryable<Brewery>()
.Where(airline => airline.Type == "brewery"),
innerKey => innerKey.BreweryId,
outerKey => N1Ql.Key( outerKey),
(inner,outer) => new { Inner = inner, Outer = outer})
.Take(1)
.ToList();

.NET SDK: N1QL Query (Linq2Couchbase)
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// Query syntax
var query =
from beer in QueryFactory.Queryable<Beer>(mockBucket.Object)
join breweryGroup in QueryFactory.Queryable<Brewery>(mockBucket.Object)
on beer.BreweryId equals N1Ql.Key(breweryGroup) into bg
from brewery in bg.DefaultIfEmpty()
select new { beer.Name, beer.Abv, BreweryName = brewery.Name };

https://github.com/couchbaselabs/N1QL-Intro-dotNET-
Supplement-Demo-code

Couchbase Developer Portal
developer.couchbase.com
80

Forums
http://forums.couchbase.com
81

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