MongoDB: Intro & Application for Big Data

Nov 18, 201119 likes4,902 views

The document discusses NoSQL databases and MongoDB in particular. It provides examples of MongoDB documents with different data types like objects, arrays, etc. It also shows how data is stored across multiple shard servers and accessed via mongos query routers. Configuration servers store sharded cluster metadata. Log data can be stored in MongoDB but only aggregated results data may be needed. HDFS is better for temporary raw log storage.

MongoDB: Intro & Application for Big Data

http://blog.nahurst.com/visual-guide-to-nosql-systems

${ "_id" : ObjectId("4dcd3ebc9278000000005158"), "timestamp" : ISODate("2011-05-13T14:22:46.777Z"), "binary" : BinData(0,""), "string" : "abc", "number" : 3, "subobj" : {"subA": 1, "subB": { "subsubC": 2 }}, "array" : [1, 2, 3], "dbref" : [_id1, _id2, _id3] }$

${ "_id" : ObjectId("4dcd3ebc9278000000005158"), "nickname" : "doryokujin" },{ "_id" : ObjectId("4dcd3ebc9278000000005159"), "firstname" : "Takahiro", "lastname" : "Inoue", "mail" : "mr.stoicman@gmail.com", "twitter" : "@doryokujin" },...$

${ "_id" : ObjectId("4dcd3ebc9278000000005158"), "timestamp" : ISODate("2011-05-13T14:22:46.777Z"), "binary" : BinData(0,""), "string" : "def", "number" : 4, "subobj" : {"subA": 1, "subB": 2 }, "array" : [1, 2, 3, 4, 5, 6], "newkey" : "In-place" }$

Cluster
Shard Servers (Data)
config Servers
(Shard Configration) shard1 shard2 shard3
[ a, f ) [ k, n) [ o, t ) Chunk
[ f, k ) [ n, o ) [ t, } )

mongos Servers (Routers)

Shard

1
( mongos
primary primary
)
Shard

cinfig Shard
mongos

Every Server:
Large HDD(500GB )
Large Memory(16GB )

Slave Delay in Master Data on
Preparation for AmazonS3
User Error

Master Data on S3
Non Sharding,
Replica Set

From Text Logs: (Large)
From mySQL: (Small)
From Other NoSQL: (Middle)

Temporary Raw data storage
is HDFS, not MongoDB

We only need result data
to discover new features

Reduction

First Second
Aggregation Aggregation

Fluent
Structured logging

Pluggable architecture

Reliable forwarding
e Event Collector Service

Fluent
Structured logging

Pluggable architecture

Reliable forwarding
e Event Collector Service

Sadayuki Furuhashi
Treasure Data, Inc.
@frsyuki

$“2011-04-01 host1 myapp: cmessage size=12MB user=me” 2011-04-01 myapp.message { “on_host”: ”host1”, 2011-04-01 myapp.message { ”combined”: true, “on_host”: ”host1”, ”combined”: true, “size”: 12000000, “size”: 12000000, “user”: “me” “user”: “me” } }$

aggregate aggregate aggregate aggregate

log log log log

key1 key2 key3 shufﬂe

aggregate aggregate aggregate

aggregate

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6. http://blog.nahurst.com/visual-guide-to-nosql-systems

9. { "_id" : ObjectId("4dcd3ebc9278000000005158"), "timestamp" : ISODate("2011-05-13T14:22:46.777Z"), "binary" : BinData(0,""), "string" : "abc", "number" : 3, "subobj" : {"subA": 1, "subB": { "subsubC": 2 }}, "array" : [1, 2, 3], "dbref" : [_id1, _id2, _id3] }

10. { "_id" : ObjectId("4dcd3ebc9278000000005158"), "nickname" : "doryokujin" },{ "_id" : ObjectId("4dcd3ebc9278000000005159"), "firstname" : "Takahiro", "lastname" : "Inoue", "mail" : "[email protected]", "twitter" : "@doryokujin" },...

11. { "_id" : ObjectId("4dcd3ebc9278000000005158"), "timestamp" : ISODate("2011-05-13T14:22:46.777Z"), "binary" : BinData(0,""), "string" : "abc", "number" : 3, "subobj" : {"subA": 1, "subB": 2 }, "array" : [1, 2, 3], padding }

12. { "_id" : ObjectId("4dcd3ebc9278000000005158"), "timestamp" : ISODate("2011-05-13T14:22:46.777Z"), "binary" : BinData(0,""), "string" : "def", "number" : 4, "subobj" : {"subA": 1, "subB": 2 }, "array" : [1, 2, 3, 4, 5, 6], "newkey" : "In-place" }

16. { "_id" : ObjectId("4dcd3ebc9278000000005158"), "timestamp" : ISODate("2011-05-13T14:22:46.777Z"), "binary" : BinData(0,""), "string" : "abc", "number" : 3, "subobj" : {"subA": 1, "subB": 2 }, "array" : [1, 2, 3], }

26. Cluster Shard Servers (Data) config Servers (Shard Configration) shard1 shard2 shard3 [ a, f ) [ k, n) [ o, t ) Chunk [ f, k ) [ n, o ) [ t, } ) mongos Servers (Routers)

27. Shard 1 ( mongos primary primary ) Shard cinfig Shard mongos

35. Every Server: Large HDD(500GB ) Large Memory(16GB ) Slave Delay in Master Data on Preparation for AmazonS3 User Error Master Data on S3 Non Sharding, Replica Set

38. From Text Logs: (Large) From mySQL: (Small) From Other NoSQL: (Middle) Temporary Raw data storage is HDFS, not MongoDB We only need result data to discover new features

39. Reduction First Second Aggregation Aggregation

40. ScientiﬁcPython

41. Fluent Structured logging Pluggable architecture Reliable forwarding e Event Collector Service

42. Fluent Structured logging Pluggable architecture Reliable forwarding e Event Collector Service Sadayuki Furuhashi Treasure Data, Inc. @frsyuki

43. “2011-04-01 host1 myapp: cmessage size=12MB user=me” 2011-04-01 myapp.message { “on_host”: ”host1”, 2011-04-01 myapp.message { ”combined”: true, “on_host”: ”host1”, ”combined”: true, “size”: 12000000, “size”: 12000000, “user”: “me” “user”: “me” } }

46. log log log log

48. aggregate aggregate aggregate aggregate log log log log key1 key2 key3 shufﬂe aggregate aggregate aggregate aggregate

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