MongoDAO Base

With an object extending MongoDAO class all functions on a specific MongoCollection can be easily used.

Base Functions like

• drop
• count
• createIndex

are implemented.

Search Functions, CRUD Functions, Find-and-Modify, and Change Streams are available.

Additional Features

Synchronous Result

All functions support synchronous result handling.

Use package import

import dev.mongocamp.driver.mongodb._

and append

• .result() for Single Result object
• .resultList() for List result object

or use implicit conversion:

def restaurantsSize: Long = RestaurantDAO.count()

Raw Support

Sometimes we need Raw Support (DAO maps to Document). This is automatically included in the MongoDAO class. Simply call Raw on your DAO Object.

val pipeline = List(filterStage, groupStage, sortStage)

val aggregated = PersonDAO.Raw.findAggregated(pipeline).resultList()

Base Functions

Drop

Drop Collection.

def drop(): SingleObservable[Unit]

Count

Count of collection with optional filter.

def count(filter: Bson = Document()): Observable[Long]

Indexes

def createIndex(key: Bson, options: IndexOptions = IndexOptions()): SingleObservable[String]

// Simple Index creation
def createIndexForField(field: String, sortAscending: Boolean = true): SingleObservable[String]

def dropIndex(keys: Bson): SingleObservable[Unit]

// Simple Index delete
def dropIndexForName(name: String): SingleObservable[Unit]

Column Names

Detect the field names present in a collection (uses an aggregation pipeline internally):

def columnNames(sampleSize: Int = 0, maxWait: Int = DefaultMaxWait): List[String]

Pass sampleSize > 0 to scan only a random sample for better performance on large collections.

Import JSON

Bulk-import a newline-delimited JSON file (one document per line):

def importJsonFile(file: better.files.File): SingleObservable[BulkWriteResult]