Connecting to a Database

This section explains how to connect to a natively supported Database.

Overall Sequence

To connect to a remote Database using DirectQuery you need to complete these steps:

1. Configure your remote Database in Atoti Market Risk's expected Database format
2. Set the Atoti Market Risk configuration properties
3. Deploy Atoti Market Risk in Horizontal Distribution

Database Schema

Required DirectQuery Properties

Disable Other Cubes

application.yaml:

mr.enable.cubes.<cube>=false

Command-line argument:

-Dmr.enable.cubes.<cube>=false

Database Configuration

Properties for enabling and connecting to a remote database can be defined using either the YAML or standard property formats. These properties can be used in .yaml and .properties files, or on the command line.

starter:
  deployment:
    type: direct-query
# MSSQL Database Connection Parameters
directquery:
  withAdjustments: false
  database:
    type: mssql
    mssql:
      username: YOUR_USERNAME
      password: YOUR_PASSWORD
      port: YOUR_PORT
      hostName: YOUR_HOST
      database: YOUR_DATABASE
      schema: YOUR_SCHEMA
      encrypt: true/false
      trustServerCertificate: true/false
      connectRetryCount: 5

starter:
  deployment:
    type: direct-query
# Snowflake Database Connection Parameters
directquery:
  database:
    type: snowflake
    snowflake:
      connectionString: YOUR_JDBC_SNOWFLAKE_CONNECTION_STRING
      username: YOUR_USERNAME
      password: YOUR_PASSWORD
      warehouse: YOUR_WAREHOUSE
      feedingWarehouse: YOUR_FEEDING_WAREHOUSE
      database: YOUR_DATABASE
      schema: YOUR_SCHEMA
      role: YOUR_ROLE
      arrayAggWrapperFunctionName: YOUR_SPECIFIC_ARRAY_AGGREGATE_FUNCTION
      additionalOptions:
        anSFSessionProperty: YOUR_EXTRA_PROPERTY 

Deployment Options

We provide two main options to run with DirectQuery:

Horizontal Distribution

In Horizontal Distribution you have access to the in-memory tools such as What-If, data updates and Sign-Off for the data loaded in-memory as well as access to a large number of historical dates.

When running in Horizontal Distribution you need to run three Nodes:

• Query node
• In-memory data node
• DirectQuery data node

mr.data-load.initial-business-dates

For both Combined in-memory query node and DirectQuery data node, set the mr.data-load.initial-business-dates property.

Given that the data nodes are distributed by AsOfDate, no two data nodes can contain the same Partition - meaning that one AsOfDate cannot be present in another node. So to prevent any issues the directQueryDatesToIncludeFilter bean is used to set which dates to include in the DirectQuery data node.

JVM With Query Node And In-Memory Data Node

This JVM consists of two distributed nodes; a query node and an in-memory data node.

Start the JVM by specifying the following parameters to the Atoti Market Risk application, either in a .properties file or through command-line arguments (add -D before each property).

See Activating and de-activating cubes for details about the enabling/disabling of cubes.

# Enable / Disable cubes
mr:
  enable:
    cubes:
      <cube>: false
      common: true

# Set MR to run this JVM with a query node and in-memory data node
starter:
  deployment:
    type: in-memory
    transport: netty

JVM With DirectQuery Data Node

Once the JVM with the query and in-memory data node is running, you can start a second JVM with the DirectQuery data node with the following configuration properties either in a .properties file or through command-line arguments (add -D before each property).

# Set MR to run as a data node and to connect to the second JVM
starter:
  deployment:
    type: direct-query
    transport: netty

# Disable cubes 
mr:
  enable:
    cubes:
      common: false
      <cube>: false 
# Use a different Content Server for this JVM
  application:
    content-service:
      db:
        url: jdbc:h2:mem:content_service;DB_CLOSE_DELAY=-1
        hibernate:
          hbm2ddl:
            auto: create
  
# Use a different port from the second JVM
server:
  port: 10011

# Enable and configure the MSSQL DirectQuery Database
directquery:
  database:
    type: mssql
    mssql:
      username: YOUR_USERNAME
      password: YOUR_PASSWORD
      port: PORT_MSSQL_DATABASE_IS_ON
      hostName: HOST_OF_THE_MSSQL_DATABASE
      database: YOUR_DATABASE_NAME
      schema: YOUR_DATABASE_SCHEMA
      encrypt: true/false
      trustServerCertificate: true/false
      connectRetryCount: integer

# Set MR to run as a data node and to connect to the second JVM
starter:
  deployment:
    type: direct-query
    transport: netty

# Disable cubes
mr:
  enable:
    cubes:
      common: false
      <cube>: false
  # Use a different Content Server for this JVM
  application:
    content-service:
      db:
        url: jdbc:h2:mem:content_service;DB_CLOSE_DELAY=-1
        hibernate:
          hbm2ddl:
            auto: create
            
# Use a different port from the second JVM
server:
  port: 10011

# Enable and configure the Snowflake DirectQuery Database
directquery:
  database:
    type: snowflake
    snowflake:
      connectionString: YOUR_JDBC_SNOWFLAKE_CONNECTION_STRING
      username: YOUR_USERNAME
      password: YOUR_PASSWORD
      role: ROLE_TO_USE
      warehouse: YOUR_WAREHOUSE
      database: YOUR_DATABASE
      schema: YOUR_SCHEMA

Single JVM

You can run a single JVM consisting of only DirectQuery.

By running in a single JVM with DirectQuery only, you can now see the DirectQuery data in the VaR/ES cube.

Properties

To run the Single JVM node you only need to configure the Database Properties and disable cubes and run the application as normal. There are no distributed nodes to configure when running in a single JVM.

See Activating and de-activating cubes for details about the enabling/disabling of cubes.

Here is an example of the properties to use:

starter:
  deployment:
    type: direct-query
    transport: local

# Disable cubes
mr:
  enable:
    cubes:
      <cube>: false
      
# Enable and configure the MSSQL DirectQuery Database
directquery:
  database:
    type: mssql
    mssql:
      username: YOUR_USERNAME
      password: YOUR_PASSWORD
      port: PORT_MSSQL_DATABASE_IS_ON
      hostName: HOST_OF_THE_MSSQL_DATABASE
      database: YOUR_DATABASE_NAME
      schema: YOUR_DATABASE_SCHEMA
      encrypt: true/false
      trustServerCertificate: true/false
      connectRetryCount: integer

starter:
  deployment:
    type: direct-query
    transport: local
    
# Disable cubes
mr:
  enable:
    cubes:
      <cube>: false

# Enable and configure the Snowflake DirectQuery Database
directquery:
  database:
    type: snowflake
    snowflake:
      username: YOUR_USERNAME
      password: YOUR_PASSWORD
      role: YOUR_ROLE
      connectionString: YOUR_CONNECTION_STRING
      warehouse: YOUR_WAREHOUSE
      database: YOUR_DATABASE_NAME
      schema: YOUR_SCHEMA_NAME
      arrayAggWrapperFunctionName: YOUR_ARRAY_AGGREGATOR_FUNCTION

Single JVM Limitations

By running DirectQuery with a single JVM you will be running purely on DirectQuery. This will come at the compromise of query performance of Trade level queries while also not having access to in-memory only tools such as WhatIf and SignOff.

Reference Database