How to use the new Domino Query Language

By Tim Davis – Director of Development.

Before I talk about building a Domino-based API gateway on Node.js, I thought it would be a good idea to expand a little on how to use the new Domino Query Language (DQL) to run queries on Domino documents.

DQL is the new query language that comes with Domino 10. It is separate from the other query syntaxes in Domino, such as the Full Text Search syntax, or @formula selection criteria. You can use it in other places than Node.js, such as LotusScript and Java, and you can even test your queries from the command line.

What is cool about DQL is that it runs using the new Design Catalog system database, GQFdsgn.nsf. This does a lot of heavy lifting in the background with pre-built design data which makes running the queries more efficient. I am told this will not always be part of the DQL engine, but for now you do need it.

The DQL processing engine also does clever prioritizing of the components of the query to make the process as efficient as possible. You can see how this is done using the ‘explain’ tool (see below).

The syntax is pretty straight-forward. Here are some simple examples to give you an idea:

customer = 'Bob Smith'

age > 21

form = 'Person' and type = 'Client'

You have all the usual operators such as =, >, <, <=, >=, and, or, not. You can wrap elements in parentheses ( ) to control the precedence.

String values are enclosed in single quotes. You can duplicate quotes in your strings to escape them, e.g.:

name = 'James O''Brien'

You can also use lists with the ‘in’ operator, like this:

form = 'Person' and type in ( 'Client', 'Supplier', 'Agency' )

DQL comes with some useful built-in functions that you can use in your queries:

@Created
@ModifiedInThisFile
@DocumentUniqueID

You can search using dates, which are included using the built-in @dt function and are in RFC3339 format. This looks a bit clunky but is pretty clear once you get used to it:

@Created > @dt('2018-01-01T00:00:00+0500')

A cool feature is being able to search in view columns. You use the view name or alias and the programmatic column name, like this:

'PendingOrders'.orderNo = '000101'

These view and column searches are fast because the design analysis of the db has already been done and stored in the design catalog. However if the database isn’t in the catalog then this kind of search will fail.  Adding databases to the catalog is an optional step you would do if you want to perform this kind of query, but being in the catalog helps with the performance of regular searches as well and so is always recommended.

One thing to bear in mind is that currently you can only search on regular summary fields in the documents, which means you can’t search in rich text items yet. I am told this is coming later.

Also, if your query generates an error during the processing then you will get no results returned. You don’t get partial results (unlike some SQL behavior). This is likely not a problem provided you know to expect it.

With all of this you should have everything you need to run pretty much any query you want, with plenty of flexibility and control.

Talking of control, DQL comes with a command line DomQuery tool to test your queries. It has an -e (explain) option that will deconstruct how your query will be processed and details how it will perform. It splits out each element of the search and lists the order they are processed, how long each takes, and how the results get filtered down step by step. You can use this to test out your searches and tune them to make sure they run efficiently and perform well for the users.

However, just in case you do end up running a query that gets out of hand there are limits to protect the server. The limits are:

  • MaxDocsScanned – maximum allowable NSF documents scanned ( 200000 default)
  • MaxEntriesScanned – maximum allowable index entries scanned (200000 default)
  • MaxMsecs – maximum time consumed in milliseconds ( 120000 ) (2 minutes)

You can override these limits system-wide using notes.ini settings if you need to, but you really ought to instead review your query’s behaviour before you consider doing this.

The DQL engine is continuously being enhanced and the new Domino 10.0.1 version adds support for query arguments (also known as substitution variables). You use query arguments when building your queries to help avoid code injection. This works by defining specifically which elements of a query are user input rather than just constructing the query as one string. Without this, a user could maliciously input some DQL syntax into the query and access unexpected documents or data.

I hope all this helps give you an idea of how easy and fast it will be to run DQL queries from a Node.js app. In my next post I plan to bring this together with the domino-db module and build an API gateway.

Using Node.js to access Domino

You will be pleased to hear that the Domino 10 module for Node.js is now in beta (you can request early access here) and in this article I would like to show you how easy it will be to use.

Before we get started using the Domino module in Node, we do need to do some admin stuff on our Domino server. It has to be running Domino 10 and we have to install the Proton add-in, and we also have to create the Design Catalog including at least one database. (The Proton add-in listens on its own port, by default 3002, and is separate from HTTP.)

More detail on these admin tasks will be covered in a companion blog, but here I would like to focus on the app-dev side.

Lets build a simple Node.js system that will read some Domino documents and get field values, and also create some new documents. In my next post we can integrate this into the basic Node stack we developed in my previous post to create an actual API.

Assuming our Domino server is all set up, the first thing we do is install the new dominodb module. When this goes live later in the year, we will do this with the usual  ‘npm install dominodb’, but while we are still in beta we install it from the downloaded beta package:

npm install ../packages/domino-domino-db-1.0.0.tgz --save

Once we have the dominodb connector installed, we can use it in our Node server.js code. The sequence is almost exactly the same as in LotusScript. First, we connect to Domino and open the Server (sort of equivalent to a NotesSession), then from this we open our Database, and then using the Database we can access and update Documents.

We start the same way as with all other Node.js modules, with a ‘require’:

const { useServer } = require('@domino/domino-db');
This ‘useServer’ is a function and is going to create our server connection. We give it the Domino server’s hostname and the Proton port, and it connects to our server like this:
serverConfig = {
    hostName: 'server.mydomain.com',
    connection: { port:'3002'}
};
useServer( serverConfig )
The useServer function returns a ‘server’ object. This is inside a javascript promise (I talked about promises in an earlier post), so we can use the server object inside the promise to open our database like this:
useServer( serverConfig ).then( async server => {
    const database = await server.useDatabase( databaseConfig );
The databaseConfig contains the filepath of our database on the server:
const databaseConfig = {
    filePath: 'orders.nsf'
};

Notice how we are using ‘async await’ to simplify the asynchronous nature of getting the database. This code looks very similar to the LotusScript equivalent.

So we have created a server connection and opened a database. Now we want to get some documents.

The domino-db module uses the new Domino Query Language (DQL) which comes with Domino 10. This can perform very efficient high-performance queries on Domino databases.

It is very much like getting a document collection with a db.search( ) in LotusScript, and the query syntax is similar to selection formulas, for example:

const coll = await database.bulkReadDocuments({
    query: "Form = 'Order' and Customer = 'ACME'"
});
This returns a collection of documents in a JSON array. These documents do not automatically contain all the items from the Notes documents. By default they only have some basic metadata, i.e. unid, created date, and modified date:
{
  "documents":[
    {
      "@unid":"A2504056F3AF6EFE8025833100549873",
      "@created": {"type":"datetime","data":"2018-10-25T15:24:00.51Z"},
      "@modified": {"type":"datetime","data":"2018-10-25T15:24:00.52Z"}
    }
  ],
  "errors":0,
  "documentRange":{"total":1,"start":0,"count":1}
}
To get field data from the documents, you need to specify which fields you want returned, and this is done with an array of itemNames:
const coll = await database.bulkReadDocuments({
  query: "Form = 'Order' and Customer = 'ACME'",
  itemNames: ['OrderNo', 'Qty', 'Price']
});
Then you get the field data included in your query results:
{
"documents":[
  {
    "@unid":"A2504056F3AF6EFE8025833100549873",
    "@created":{"type":"datetime","data":"2018-10-25T15:24:00.51Z"},
    "@modified":{"type":"datetime","data":"2018-10-25T15:24:00.52Z"},
    "OrderNo":"001234",
    "Qty":2,
    "Price":25.49
  }
],
"errors":0,
"documentRange":{"total":1,"start":0,"count":1}
}
We can output the document field data with JSON dot notation in a console.log (with the JSON.stringify method to format it properly):
console.log( "Order No: " + JSON.stringify( coll.documents[0].OrderNo ) );

So this is how to read a collection of documents. Now lets look at creating a new document, which is even easier.

First we build our document data in an ‘options’ object, including the Form name and all our other item values:

const newDocOptions = {
  document: {
    Form: 'Order',
    Customer: 'ACME',
    OrderNo: '000343',
    Qty: 10,
    Price: 49.99
  }
};
Then we simply call the ‘createDocument’ method, like this:
const unid = await database.createDocument( newDocOptions );

We don’t need to call a ‘save’ on the document, it is all handled in one operation. The return value is the unid of the newly-created document, so we can act on it again to update it if we want to.

To update a document, we get it by its unid with the ‘useDocument’ method, and then we can call ‘replaceItems’ on it.

This takes the new values in a ‘replaceItems’ parameter, but it only needs to contain the fields to update:

const document = await database.useDocument({
  unid: coll.documents[0]['@unid']
});
await document.replaceItems({
  replaceItems: { Qty: 11 }
});

Here we are using the ‘@unid’ value from the collection we got earlier. This is a bit fiddly because ‘@’ is a reserved symbol in JSON, but we can use the JSON square bracket notation to get around this.

We have got documents and created and updated documents. In addition to all these, the domino-db module provides a variety of methods for reading, creating and updating documents, allowing you to do anything you would need.

Also, the DQL syntax has sophisticated search facilities that can return large numbers of documents and can even search in views and columns.

There are couple of things to be aware of:

The first is that by default the connection to Domino is unsecured, but you can easily make it use TLS/SSL. You may need help from your Domino admin to provide you with the certificate and key files, but this is all explained in the documentation.

The second thing is that currently this access is either Anonymous or can be set to a single Domino user account in TLS/SSL by the client certificate (which maps to a Domino person document). So in the beta there is no user authentication per se, but this will be coming later with OAuth support.

I hope you found this both useful and exciting. In my next article I plan to show how to build these domino-db methods into a Node HTTP server and create an API gateway.