dcdb overview of stored procedures

dcDB Stored Procedures:An Overview

DivConq Framework’s MUMPS API

Connectivity and FlowOverview of DivConq database handling and Request-Response flow

Linux BoxLinux, Windows or OS X Box

Connectivity

Java Appw/ DivConq

MUMPSSSH

Java code connects to the MUMPS database via an SSH connection. This keeps the data secure while in transit.

Linux Box

Local Connectivity

Java Appw/ DivConq

MUMPSSSH

Of course there is no reason why Java cannot run on the same box. SSH is still used, connecting over the loopback network interface.


Channels

Java Appw/ DivConq

MUMPSSession

One SSH session is used. Multiple SSH channels enable greater throughput.Typically DivConq uses three channels, which creates three MUMPS processes.

Channels


Request-Response

Java Appw/ 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.

Request Structure

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.

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 }

Request Flow, Step 1

Java Appw/ DivConq

MUMPS

#1 - Your code builds a request and submits it. Request submission is asynchronous, so you also must provide a callback to handle the result.

DivConq Database Interface

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DivConq Schema

Request Verifier

Response

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#2 – Your request is verified, including validating the parameters with what is declared in the schema.


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#3 – If verification passes your request is put on to the request queue.


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#3


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#4 – When a database worker (channel) is available, it takes the request from the queue and sends it to MUMPS.


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Response Flow, Step 5

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#5 – That worker then reads (blocking) the result and any accompanying debug/error messages.


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#4and#5


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#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.


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#6


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MUMPS

#7 – The response and any debug/error messages are delivered to your code via a the callback you provided at submission.


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JavaRequest-Response handling within Java

Request in Java, Step 1

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.

Example

RecordStruct ages = new RecordStruct();ages.setField("MinAge", 3);ages.setField("MaxAge", 8);


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.

Example

RecordStruct ages = new RecordStruct();ages.setField("MinAge", 3);ages.setField("MaxAge", 8); QueryRequest request = new QueryRequest("dctListPeople", ages);


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.

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());

}};


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.

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);

Request-Response in Schema

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”.

<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>

Request-Response in Schema

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.

<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>

Request-Response Example

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.

Request (Params) Examples

a: { “MinAge”: 30, “MaxAge”: 48 }b: { “MaxAge”: 48 }c: null

Response Examples

a: [ “Jim”, “Beth”, “Sandy” ]b: [ ]

Linux Box

Why the Focus on JSON

Java App w/ DivConq MUMPS

There are many reasons to “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.


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MUMPSProcess

MUMPSProcess

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Schema

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MUMPSRequest-Response handling within MUMPS

Request in MUMPS

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.

Java Request (Params)

{ “MinAge”: 30, “MaxAge”: 48 }

MUMPS Params

Params(“MinAge”)=30Params(“MaxAge”)=48

MUMPS Procedure

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.

Schema Declaration

<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

MUMPS Procedure Logic

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.

listPeople n id,minage,maxage,age 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 . s age=^dctData("People",id,"Age") . i (minage'="")&(age<minage) q . i (maxage'="")&(age>maxage) q . w ScalarStr_^dctData("People",id,"Name") ; w EndList ; end list of people ; quit

Result in Java

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.

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());

}};

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.

dcdb overview of stored procedures

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