The document is a presentation from Percona Live London 2013 by Robert Hodges and Tim Callaghan about transitioning from MySQL to MongoDB. It details the differences in schema design, querying, data management, replication, sharding, and security between the two databases, along with practical coding examples. The session emphasizes understanding MongoDB's unique features and potential challenges for users familiar with MySQL.

1. Use Your MySQL Knowledge to
Become a MongoDB Guru
Percona Live London 2013
Robert Hodges
CEO
Continuent
Tim Callaghan
VP/Engineering
Tokutek
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Tuesday, November 12, 13

2. Our Companies
Robert Hodges
• CEO at Continuent
• Database nerd since 1982 starting with M204, RDBMS since
1990, NoSQL since 2012; designed Continuent Tungsten
•
Continuent offers clustering and replication for MySQL and
other fine DBMS types
Tim Callaghan
• VP/Engineering at Tokutek
• Long time database consumer (Oracle) and producer (VoltDB,
Tokutek)
•
Tokutek offers Fractal Tree indexes in MySQL (TokuDB) and
MongoDB (TokuMX)
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3. MongoDB -- The New MySQL
One Bad Thing about
MongoDB
One Good Thing about
MongoDB
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4. One Bad Thing about MongoDB
MySQL
> select * from table1 where column1 > column2;
> ... 5 row(s) returned
MongoDB
> db.collection1.find({$field1: {gt: $field2}});
> ReferenceError: $field2 is not defined
[current] MongoDB query language is
<field> <operator> <literal>
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5. One Good Thing about MongoDB
Robert’s “ease of use”
demo
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6. Today’s Question
How can you use your
MySQL knowledge to get
up to speed on MongoDB?
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7. Topic:
Schema Design
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8. How Do I Find Things in MongoDB?
mongod server
== mysqld
== MySQL schema
== MySQL table
~ Sort of like a MySQL row
!= MySQL column
database
collection
BSON document
key/value pair
key/value pair
key/value pair
BSON document...
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9. How Do I Create a Table and Insert Data?
Connect
# Ruby Code
MongoClient.new("localhost").
db("mydb").
Use database
collection("sample").
insert({"data" => "hello world"})
Choose
collection
Insert data to
materialize database
and collection
Primary key
generated
automatically
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10. How Do I Change the Schema?
# Ruby Code
MongoClient.new("localhost").
db("mydb").
collection("sample").
insert({"data" => "hello again!",
"author" => “robert”})
Just add
more data
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11. How Do I Validate Schema?
rs0:PRIMARY>
{ "_id" : 1,
{ "_id" : 2,
{ "_id" : 3,
db.samples.find()
"data" : "hello world" }
"daata" : "bye world” }
"data" : 26.44 }
Software bugs?
rs0:PRIMARY> show databases
local ! 2.0771484375GB
mydb! 7.9501953125GB
Typo from an
mydb1! 0.203125GB
early run
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12. How Do I Remove Data? (Part 1)
Drop a database
rs0:PRIMARY> db.dropDatabase()
{ "dropped" : "mydb", "ok" : 1 }
Drop a collection
rs0:PRIMARY> db.samples.drop()
true
Drop a column?
rs0:PRIMARY> db.foo.update(
{ author: { $exists: true }},
{ $unset: { author: 1 } },
false, true )
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13. How Do I Remove Data? (Part 2)
(Remove documents based on TTL index)
> db.samples.ensureIndex(
{"inserted": 1},
{"expireAfterSeconds": 60})
> db.samples.insert(
{"data": "hello world",
inserted: new Date()})
> db.table.count()
1
...
> db.table.count()
0
(Capped collections do same with space)
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14. How Does MongoDB Do Joins?
It Doesn’t!
(It is your job to denormalize or do
application level joins. This includes
thinking about storage.)
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15. Topic:
Data Storage
and Organization
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16. How is My Data Stored, Logically?
MongoDB storage is very similar to MyISAM
secondary
index(es)
_id index
etc.
collection data (documents)
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17. How is My Data Stored, Physically?
But it does look different in the file system.
MyISAM
<db>/<table>.frm
<db>/<table>.myd
<db>/<table>.myi
MongoDB
<db1>.ns
<db1>.1 .. <db1>.n
<db2>.ns
<db2>.1 .. <db2>.n
• start MongoDB with “--directoryperdb” to put
files in database folders
• pro-tip : do this to gain IOPs by database
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18. How Much Memory Does It Use?
All of it!
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19. How does MongoDB Manage Memory?
• MyISAM
– key_cache_size determines index caching
– data is cached in Operating System buffers
• InnoDB
– innodb_buffer_pool_size determines index/data
caching
• MongoDB
– memory mapped files
– mongod grows to consume available RAM
– good : no knob
– bad : operating system is in charge of cache
– bad : available RAM may change over time
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20. How Will It Perform for My Workload?
• It depends...
– Determine your “working set”
o The portion of your data that clients access most often
o db.runCommand( { serverStatus: 1, workingSet: 1 } )
– If working set <= RAM
o Performance generally very good
o Be careful in high-concurrent-write use cases
– If working set >= RAM
o Likely IO bound
o Sharding to the rescue!
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21. How Can Schema Affect Working Set?
• Field names are stored with the document
– On disk and in memory
• Plan ahead, specially for large collections
BAD!
GOOD!
{ first_name: “Timothy”,
middle_initial: “M”,
last_name: “Callaghan”,
address_line_1: “555 Main Street”,
address_line_2: “Apt. 9” }
{ fn: “Timothy”,
mi: “M”,
ln: “Callaghan”,
al1: “555 Main Street”,
al2: “Apt. 9” }
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22. Topic:
Query Optimization
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23. How Does the Query Optimizer Work?
• MySQL
– Optimizer find useable indexes for the query
– For each index, optimizer asks the storage engine
o What is the cardinality for the given keys?
o What is the estimated cost?
– The “best” plan is chosen and used for the query
• This occurs for every single query
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24. How Does the Query Optimizer Work?
• MongoDB
– All candidate indexes run the query in parallel
o “candidate” meaning it contains useful keys
– As matching results are found they are placed in a
shared buffer
– When one of the parallel runs completes, all
others are stopped
– This “plan” is used for future executions of the
same query
o Until the collection has 1,000 writes, mongod restarts, or
there is an index change to the collection
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25. A Simple Yet Elegant Solution?
• No more wrestling with the optimizer
• Hints are supported ($hint)
– Force a particular index
– http://docs.mongodb.org/manual/reference/
operator/meta/hint/
• Easier since MongoDB does not support joins
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26. Topic:
Transactions
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27. MySQL Transactions and Isolation
InnoDB creates
MVCC view of data;
locks updated rows,
commits atomically
mysql> BEGIN;
...
mysql> INSERT INTO sample(data) VALUES
(“Hello world!”);
mysql> INSERT INTO sample(data) VALUES
(“Goodbye world!”);
...
mysql> COMMIT;
MyISAM locks table
and commits each
row immediately
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28. How Does MongoDB Implement Locking?
# Update data ranges of documents to
# show effects of database lock.
@col.update(
{key =>
Locks database
{"$gte" => first.to_s,
"$lt" => last.to_s}
},
{ "$set" =>
{ "data.x" => rand(@rows)}})
Test
Total Requests/Sec
Single thread updating single collection
Two threads updating two collections, same DB
Four threads updating two collections, same DB
Two threads updating two collections, different DBs
197
80 + 80 = 160
29+29+30+30 = 118
190 + 179 = 369
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29. How Does MongoDB Implement Isolation?
• MongoDB does not prevent threads from
seeing partially committed data
• Example: Index changes can result in “double
read” of data if query uses index while index
is changing
• Experiment: Construct a test to:
• Select from numeric index and count rows
• Simultaneously update index to shift lower
values past end of previous high value
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30. How Does MongoDB Implement Isolation?
# Select values.
count = 0
@col.find(“k1” =>
{"$gte" => 120000}).
each do |doc|
count += 1
end
puts "Count=#{count}"
# Run update to increase.
@col.update(
{"_id" =>
{"$exists" => true}},
{"$inc" =>
{“k1” => increment}},
{:multi => true})
Count=50000
Count=50000
Count=100000 <--Index shifts over tail
Count=50000
Count=50000
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31. Topic:
Replication and HA
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32. Review of MySQL Replication
Master
Slave
Master-master
configuration
for fast failover
Relay
Log
Binlog
Relay
Log
set global
read_only=1;
Binlog
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33. How Does MongoDB Set Up Replication?
PRIMARY
Replication
SECONDARY
Heartbeat
Heartbeat
Replication
SECONDARY
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34. Where Is The Replica Set Defined?
$ mongo localhost
...
# rs0:PRIMARY> rs.config()
{
!
"_id" : "rs0",
!
"version" : 8,
!
"members" : [
!
! {
!
! ! "_id" : 0,
!
! ! "host" : "mongodb1:27017"
!
! },
!
! {
!
! ! "_id" : 1,
!
! ! "host" : "mongodb2:27017"
!
! },
!
! {
!
! ! "_id" : 2,
!
! ! "host" : "mongodb3:27017”
!
! }
!
]
}
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35. How Do Applications Connect?
# Connect to MongoDB replica set.
client = MongoReplicaSetClient.new(
['mongodb1', 'mongodb2', 'mongodb3'])
# Access a collection and add data
db = client.db("xacts")
col = db.collection("data")
col.insert({"data" => "hello world"})
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36. How Do You Read From a Slave?
# Connect to MongoDB replica set.
client = MongoReplicaSetClient.new(
['mongodb1', 'mongodb2', 'mongodb3'],
:slave_ok => true)
# Access a collection and select documents.
db = client.db("xacts")
col = db.collection("data")
col.find()
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37. Where’s the Binlog?
Find last document in
the OpLog
rs0:PRIMARY> use local
rs0:PRIMARY> db.oplog.rs.find().
... sort({ts:-1}).limit(1)
{ "ts" : Timestamp(1383980308, 1),
"h" : NumberLong("9112507265624716453"),
"v" : 2, "op" : "i", "ns" : "xacts.data",
"o" : {
"_id" :
ObjectId("527ddd116244f28f4592f6a8"),
"data" : "hello world!"
}
}
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38. How Do You Lock the DB to Back Up?
(= FLUSH TABLES WITH READ LOCK)
rs0:SECONDARY> db.fsyncLock()
{
! "info" : "now locked against writes, use
db.fsyncUnlock() to unlock",
! "seeAlso" : "http://dochub.mongodb.org/
core/fsynccommand",
! "ok" : 1
}
...
(tar or rsync data)
...
(= UNLOCK TABLES)
rs0:SECONDARY> db.fsyncUnlock()
{ "ok" : 1, "info" : "unlock completed" }
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39. How Do You Fail Over?
• Planned failover: update rs.config and save:
rs0:SECONDARY>
rs0:SECONDARY>
rs0:SECONDARY>
rs0:SECONDARY>
rs0:SECONDARY>
cfg = rs.conf()
cfg.members[0].priority = 1
cfg.members[1].priority = 1
cfg.members[2].priority = 2
rs.reconfig(cfg)
• Unplanned failover: kill or stop mongod
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40. Topic:
Sharding
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41. How is Partitioning Like Sharding?
• MySQL partitioning breaks a table into <n>
tables
– “PARTITION” is actually a storage engine
• Tables can be partitioned by hash or range
– Hash = random distribution
– Range = user controlled distribution (date range)
• Helpful in “big data” use-cases
• Partitions can usually be dropped efficiently
– Unlike “delete from table1 where timeField <
’12/31/2012’;”
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42. How Does Partitioning Help Queries?
Partitioned big_table on dateCol by month.
select * from big_table where column1 = 5;
Aug-2013
Sep-2013
Oct-2013
Nov-2013
select * from big_table where dateCol = ’10/12/2013’;
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43. Can I Finally Scale My Workload Horizontally?
• MySQL partitioning is helpful, but is still
constrained to a single machine
• MongoDB supports cross-server sharding
– huge plus: it’s “in the box”
– MySQL fabric is bringing something, we’ll see
– Many other 3rd Party MySQL options exist
• Only shard the collections that require it
• Each MongoDB shard is a replica set (1
primary and 1+ secondaries)
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44. What Does MongoDB Sharding Look Like?
Master
client app1
client app2
Master
...
mongosn
shard1
Slave
shard2
Slave
shardn
mongos1
...
Slave
...
Master
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45. How Does Sharding Help Queries?
Sharded big_table on dateCol by month.
select * from big_table where column1 = 5;
Aug-2013
shard... shard1
Sep-2013
Oct-2013
Nov-2013
shard2
shard3
shard4
shard...
select * from big_table where dateCol = ’10/12/2013’;
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46. How Do I Pick a Shard Key?
• MongoDB shards on one or more fields
• Simple example
– “orders” collection (customerId and productId)
– 1: shard on customerId
o each order writes to a single shard
o reads by customer on single shard
o reads by product on entire cluster
– 2: shard on productId
o each order writes to several shards
o reads by customer on entire cluster
o reads by product on single shard
– 3: store everything twice and shard both ways
o worst case for writes
o best cast for reads (either is shingle shard)
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47. Topic:
Security
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48. How Secure is It?
• basic username/password
• by database
• roles
– read = read any collection
– readWrite = read/write any collection
– dbAdmin = create index, create collection, rename
collection, etc.
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49. What About Advanced Security?
• Kerberos support in MongoDB Enterprise
Edition
• SSL is supported, but
– Note: The default distribution of MongoDB does
not contain support for SSL. To use SSL, you must
either build MongoDB locally passing the “--ssl”
option to scons or use MongoDB Enterprise.
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50. What Else is There to Learn?
• Tools - mongostat, mongo[export/
•
•
import], mongo[dump/restore]
Aggregation Framework
• Think SQL aggregate functionality
Map/Reduce
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51. What Should You Do?
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52. Summary
We liked...
• Ease of install
• Ability to just “jump in”
Look [out] for...
• Query language (Tim says hang in there!)
• You have to think about storage and queries in advance
Highly Recommended Reading
• Karl Seguin’s “The Little MongoDB Book”
• http://openmymind.net/mongodb.pdf
• MongoDB’s “SQL to MongoDB Mapping Chart”
• http://docs.mongodb.org/manual/reference/sql-comparison/
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53. Questions?
Robert Hodges
CEO, Continuent
robert.hodges@continuent.com
@continuent
Tim Callaghan
VP/Engineering, Tokutek
tim@tokutek.com
@tmcallaghan
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