MongoDB is a NoSQL database that stores data in BSON format, which is a binary encoding of JSON. It uses collections instead of tables, does not enforce schemas heavily, and queries use BSON queries. Data can be inserted, updated, and deleted from collections. Apache Hive also runs on Hadoop and uses HDFS for storage. It provides SQL-like queries using HiveQL, but organizes data into databases, tables, partitions, and buckets. Hive queries actually generate MapReduce jobs, so they can take a long time to complete for large datasets.

1. NoSQL
continued
CMSC 461
Michael Wilson

2. MongoDB
 MongoDB is another NoSQL solution
 Provides a bit more structure than a solution
like Accumulo
 Data is stored as BSON (Binary JSON)
 Binary encoded JSON, extends JSON
 Allows storage of large amounts of data

3. SQL vs. MongoDB
 SQL has databases, tables, rows, columns
 Monbo has databases, collections,
documents, fields
 Both have primary keys, indexes
 Collection structures are not enforced heavily
 Inserts automatically create schemas

4. Interacting with MongoDB
 Multiple databases within MongoDB
 Switch databases
 use newDb
 New databases will be stored after an insert
 Create collection
 db.createCollection(“collectionName”)
 Not necessary, collections are implicitly created
on insert

5. BSON
 MongoDB uses BSON very heavily
 Binary JSON
 Like JSON with a binary serialization method
 Has extensions so that it can represent data
types that JSON cannot
 Used to represent documents, provide input
to queries

6. Selects/queries
 In MongoDB, querying typically consists of
providing an appropriately crafted BSON
 SELECT * FROM collectionName
 db.collectionName.find()
 SELECT * FROM collectionName WHERE field =
value
 db.collectionName.find( {field: value} )
 SELECT * FROM collectionName WHERE field > 5
 db.collectionName.find( {field: {$gt: 5} } )
 Other functions that take a query argument have
queries that are formatted this way

7. Interacting with MongoDB
 Insert
 db.collectionName.insert( {queryBSON} )
 Update
 db.collectionName.update( {queryBSON},
{updateBSON}, {optionBSON} )
 updateBSON
 Set field to 5: {$set: {field: 5}}
 Increment field by 1 {$inc: {field: 1}}
 optionBSON
 Options that determine whether or not to create new
documents, update more than one document, write
concerns

8. Interacting with MongoDB
 Delete
 db.collectionName.remove( {queryBSON} )

9. Apache Hive
 Also runs on Hadoop, uses HDFS as a data
store
 Queryable like SQL
 Using an SQL-inspired language, HiveQL

10. Hive data organization
 Databases
 Tables
 Partitions
 Tables are broken down into partitions
 Partition keys allow data to be stored into
separate data files on HDFS
 Can query on particular partitions
 Buckets
 Can bucket by column to sample data

11. Purpose of Hive
 Provide analytics, query large volumes of data
 NOT to be used for real time queries like
Postgres or Oracle
 Hive queries take forever
 Partitions and buckets can help reduce this
amount of time

12. Hive queries
 Hive queries actually generate MapReduce
jobs
 MapReduce jobs take a while to set up and run
 MapReduce jobs can be run manually, but for
structured data and analytics, Hive can be
used