1. dcDB Stored Procedures: An Overview
DivConq Framework’s MUMPS API
dcDB Stored Procedures: An Overview

2. Connectivity Linux, Windows or OS X Box Linux Box Java App w/ DivConq
MUMPS
SSH
Java code connects to the MUMPS database via an SSH connection. This keeps
the data secure while in transit.

3. Local Connectivity Linux Box Java App SSH MUMPS w/ DivConq
Of course there is no reason why Java cannot run on the same box. SSH is still used, connecting over the loopback network interface.

4. Channels Linux, Windows or OS X Box Linux Box Java App w/ DivConq
MUMPS
Session
Channels
One SSH session is used. Multiple SSH channels enable greater throughput.
Typically DivConq uses three channels, which creates three MUMPS processes.

5. Request-Response Linux, Windows or OS X Box Linux Box Java App
w/ DivConq
MUMPS
Communication is Request-Response only, requests are originated in Java and responses are supplied by MUMPS code.
By using three channels, up to three requests can be processed at once. A long running request does not hold up other requests.

6. Request Structure Structure Name: [Stored Procedure Name]
Kind: “Update” or “Query”
Params: [any JSON-like data structure]
Example
Name: “dctListPeople”
Kind: “Query”
Params: { “MinAge”: 30, “MaxAge”: 48 }
Your code builds a request and submits it to DivConq’s database interface. A request must have a name and a kind, parameters are optional. Name = name of the stored procedure. Kind will be Update only if it changes data within the database (Insert, Update, Delete), otherwise use Query.

7. Request Flow, Step 1 Java App w/ DivConq MUMPS DivConq
Database Interface
MUMPS
Process
Request Queue
Your
Application
Code
Request Verifier
MUMPS
Process
Database Workers #1
Response Verifier
MUMPS
Process
DivConq Schema
#1 - Your code builds a request and submits it. Request submission is asynchronous, so you also must provide a callback to handle the result.

8. Request Flow, Step 2 Java App w/ DivConq MUMPS DivConq
Database Interface
MUMPS
Process
Request Queue
Your
Application
Code
Request Verifier
MUMPS
Process
Database Workers #1
Response Verifier
MUMPS
Process #2
DivConq Schema
#2 – Your request is verified, including validating the parameters with what is declared in the schema.

9. Request Flow, Step 3 Java App w/ DivConq MUMPS DivConq
Database Interface
MUMPS
Process
Request Queue #3
Your
Application
Code
Request Verifier
MUMPS
Process
Database Workers #1
Response Verifier
MUMPS
Process #2
DivConq Schema
#3 – If verification passes your request is put on to the request queue.

10. Request Flow, Step 4 Java App w/ DivConq MUMPS DivConq
Database Interface
MUMPS
Process
Request Queue #3 #4
Your
Application
Code
Request Verifier
MUMPS
Process
Database Workers #1
Response Verifier #4
MUMPS
Process #2
DivConq Schema
#4 – When a database worker (channel) is available, it takes the request from the queue and sends it to MUMPS.

11. Response Flow, Step 5 Java App w/ DivConq MUMPS DivConq
Database Interface
MUMPS
Process
Request Queue #3 #4
Your
Application
Code
Request Verifier
MUMPS
Process
Database Workers #1
Response Verifier #4
and #5
MUMPS
Process #2
DivConq Schema
#5 – That worker then reads (blocking) the result and any accompanying debug/error messages.

12. Response Flow, Step 6 Java App w/ DivConq MUMPS DivConq
Database Interface
MUMPS
Process
Request Queue #3 #4
Your
Application
Code
Request Verifier
MUMPS
Process
Database Workers #1
Response Verifier #4
and #5
MUMPS
Process #2 #6
DivConq Schema
#6 – The response is verified by validating the (JSON-like) result with what is declared in the schema. If response does not validate, error messages are added to messages collected from MUMPS.

13. Response Flow, Step 7 Java App w/ DivConq MUMPS DivConq
Database Interface
MUMPS
Process
Request Queue #3 #4
Your
Application
Code
Request Verifier
MUMPS
Process
Database Workers #1
Response Verifier #4
and #5
MUMPS
Process #7 #2 #6
DivConq Schema
#7 – The response and any debug/error messages are delivered to your code via a the callback you provided at submission.

14. Request in Java, Step 1 Example
RecordStruct ages = new RecordStruct();
ages.setField("MinAge", 3);
ages.setField("MaxAge", 8);
Parameters are composed of JSON-like structures. In DivConq use RecordStruct to compose records (aka Objects in JSON) and ListStruct to compose lists (aka Arrays in JSON). Records (aka Objects) have fields – just as in JSON – the field values may be lists, records or scalars. Above we are using numeric scalars.

15. Request in Java, Step 2 Example
RecordStruct ages = new RecordStruct();
ages.setField("MinAge", 3);
ages.setField("MaxAge", 8);
QueryRequest request = new QueryRequest("dctListPeople", ages);
Create the request object. The Name and Kind are required. Kind can be derived from the class name (QueryRequest vs UpdateRequest). Name is the first parameter to the constructor. The parameters, optionally, follow the name in the call to the constructor.

16. Request in Java, Step 3
ObjectCallback callback = new ObjectCallback() {
@Override
public void process(ObjectResult result) {
System.out.println("Messages:");
TestDb.printPretty(result.getMessages());
System.out.println();
System.out.println("Result:");
TestDb.printPretty(result.getResult()); } };
You also need to create a callback object. This example callback simply prints the messages and results to the console as JSON output. You may call “getResultAsRec” (RecordStruct) or “getResultAsList” (ListStruct) to process the result using DivConq’s JSON-like API.

17. Request in Java, Step 4 Example
RecordStruct ages = new RecordStruct();
ages.setField("MinAge", 3);
ages.setField("MaxAge", 8);
QueryRequest request = new QueryRequest("dctListPeople", ages);
ObjectCallback callback = new ObjectCallback() ...
Hub.instance.getDatabase().submit(request, callback);
Finally, to get the request to the database call the “submit” method and pass in the request and callback. Your result, even if it is just an error message, will be presented in the callback’s “process” method.

18. Request-Response in Schema
<Procedure Name="dctListPeople" Execute="listPeople^dctToyTest">
<Description>
Get a list of names of all people in test data.
Optionally apply an age range filter
</Description>
<RecRequest>
<Field Name="MinAge" Type="Integer" />
<Field Name="MaxAge" Type="Integer" />
</RecRequest>
<ListResponse Type="String" />
</Procedure>
A DivConq schema file holds custom data types, table declarations, stored procedure declarations and more. Above is just one snipped from the schema file showing the declaration for the stored procedure “dctListPeople”.

19. Request-Response in Schema
<Procedure Name="dctListPeople" Execute="listPeople^dctToyTest">
<Description>
Get a list of names of all people in test data.
Optionally apply an age range filter
</Description>
<RecRequest>
<Field Name="MinAge" Type="Integer" />
<Field Name="MaxAge" Type="Integer" />
</RecRequest>
<ListResponse Type="String" />
</Procedure>
Key elements here are the Request and Response which provide the validation rules for this procedure. Expect either a RecRequest (RecordStruct) or a ListRequest (ListStruct) for request – those are our options for request parameters. Likewise, expect a RecResponse or a ListResponse for the response.

20. Request-Response Example
Request (Params) Examples
a: { “MinAge”: 30, “MaxAge”: 48 }
b: { “MaxAge”: 48 }
c: null
Response Examples
a: [ “Jim”, “Beth”, “Sandy” ]
b: [ ]
Note that the params are not marked as required (in the schema), so any of the three examples for request are valid.
The response is a list of strings. No minimum is given, so a list of zero is valid.

21. Why the Focus on JSON Windows User w/ Web Browser Linux Box
Java App w/ DivConq
MUMPS
MUMPS
Process
Your
Application
Code
DivConq
Database Interface
MUMPS
Process
External
App on
Linux
DivConq
Web Server
(HTTP + Web Sockets)
MUMPS
Process
DivConq Schema
There are many reasons why JSON – one of the best is interoperability with web apps and other external applications. Through HTTP or WebSocket calls JSON parameters can be sent and JSON results can be returned. To minimize interoperability hassles DivConq favors JSON-like structures throughout.

22. Request in MUMPS Java Request (Params) { “MinAge”: 30, “MaxAge”: 48 }
MUMPS Params
Params(“MinAge”)=30
Params(“MaxAge”)=48
JSON can be adopted to MUMPS structures without much effort, details in a future presentation. As far as this overview is concerned, the key point is that JSON-like structures get transformed into MUMPS structures before the stored procedure is called.

23. MUMPS Procedure Schema Declaration MUMPS Code
<Procedure Name="dctListPeople" Execute="listPeople^dctToyTest">
MUMPS Code
listPeople ; ;
w StartList ; start list of people
w ScalarStr_“Jim” ; write a scalar
w ScalarStr_“Beth” ; write another scalar
w EndList ; end list of people
quit
The schema tells us what MUMPS routine and function to call. Above is a hint at what the code has to do – return a list of strings. Note how the result from the procedure is sent back to Java by using the “write” command.

24. MUMPS Procedure Logic
listPeople n id,minage,maxage
s minage=Params("MinAge"),maxage=Params("MaxAge") ;
w StartList ; start list of people (name only)
f s id=$o(^dctData("People",id)) q:id="" d
. i (minage'="")&(^dctData("People",id,"Age")<minage) q
. i (maxage'="")&(^dctData("People",id,"Age")>maxage) q
. w ScalarStr_^dctData("People",id,"Name")
w EndList ; end list of people
quit
You’ll need to review the dctToyTest routine to get the details on this example, but what you can see here is that we loop through all the people an apply the (optional) filter. People who are not filtered are returned as scalars (just names) in the list.

25. Result in Java
ObjectCallback callback = new ObjectCallback() {
@Override
public void process(ObjectResult result) {
if (result.hasErrors()) {
System.out.println("Error in List");
return; }
ListStruct names = result.getResultAsList();
for (Struct item : names.getItems())
System.out.println("Name: " + item.toString()); };
Back in Java you can process the result via ListStruct by looping all the items. We know, because of the schema validation and the call to “hasErrors” that our items are all just strings. There are a few ways to work with a string item, but certainly calling “toString” will work.

26. Conclusion
There is a lot more to learn about stored procedures, but now you have an overview of how it works as well as some of the design philosophy.