Hi all,

We are delivering files to SFTP server using EnsLib.FTP.PassthroughOperation class and EnsLib.FTP.OutboundAdapter. But we are facing error below:

ERROR <Ens>ErrFTPPutFailed: FTP: Failed to Put file '' (msg='Error in SFTP Put('/cachesys/mgr/Temp/HC4IZVmI6w9gEw.sftp','/directory1/directory2/directory3/') ERROR #7511: SFTP Error '4': SFTP Error [80102004]: Operation Failed [80102004] at SFTP.cpp:750,0',code=0).

The SFTP settings is as follows:

Basic settings:

Hi all.

I'm currently looking at a use case where I need to take a Stream, and then encode the contents as a Base64 Stream. This is currently achieved with a snippet of code that has previously been placed in multiple classes within this particular environment, and relied on the dotnet gateway (which suffers with a bug in 2022.1, corrected 2022.1.1).

I would like to integrate SQL into our ObjectScript routines in order to illustrate how SQL can be used to minimize development time. However, there are two questions I have.

1. How does one iterate through the results of a SELECT statement?
2. How does one access a Table in another namespace?

Curious if there is a string function which can transform a delimited string into an array without looping through $Piece...such as "a,b,c,d,e,f" into array(0)=5,array(1)="a",array(2)="b" etc

If I have defined a class query in one of my classes and I want to use that query from a method of another class, what are the pros and cons of using the %SQL.Statement interface versus the %Library.ResultSet interface?

I believe %SQL.Statement is the newer interface.

So if the old way is:

USER>s rs=##class(%Library.ResultSet).%New("%Library.File:FileSet")
 
USER>s sc=rs.Execute("c:\s\","*.txt")
 
USER>w sc
1
USER>while rs.%Next() {w !,rs.Data("Name")}

...

then the new way is:

IRIS and Ensemble are designed to act as an ESB/EAI. This mean they are build to process lots of small messages.

But some times, in real life we have to use them as ETL. The down side is not that they can't do so, but it can take a long time to process millions of row at once.

To improve performance, I have created a new SQLOutboundAdaptor who only works with JDBC.

BatchSqlOutboundAdapter

Extend EnsLib.SQL.OutboundAdapter to add batch batch and fetch support on JDBC connection.

I have a code block in a BPL. I have the below SQL and code. All variables have been declared and set. When I run the SQL, if there are no values returned, I get 100 for the value of SQLCODE when I perform the FETCH, which is correct. If values are returned, I get a -400 error when I perform the first FETCH. I've investigated, but cannot find the reason for a -400 error. Hoping someone out here understands this and knows what's wrong.

Hi all,

I wonder how to sync my server code to my local code using Visual Studio Code.

Previously, using Atelier, you could open a view of server and can copy the code to the current project, also if I change a BP, I could sync the code because I had a signal that It's warning me that there was a change and it needs to be updated.

I thing i shouls opening the ObjectScript: Explorer and select the code directaly, and right click -> Import and compile current file (Ctrl + F7)

If I use this command, the ouptut window shows:

Hi developers!

As you know InterSystems IRIS besides globals, object, document and XML data-models also support relational where SQL is expected as a language to deal with the data.

And as in other relational DBMS InterSystems IRIS has its own dialect.

I start this post to support an SQL cheatsheet and invite you to share your favorites - I'll update the content upon incoming comments.

Here we go!

I have an application in Cache 2013 (No Ensemble) which need to consume a REST web API over internet.

Can somebody please help me by pointing out the documentation or provide me code sample for consuming the REST API from a routine/class.

I am using Cache 2008 (No Ensemble) .

In this article I'd like to discuss asynchronous REST and approaches to implementing it.

Why do we need asynchronous REST? Simply put - answering the request takes too much time. While most requests usually can be satisfied immediately, some can't. The reasons are varied:

• You need to perform time-consuming calculations
• Performing action actually takes time (for example container creation)
• etc.

The solution to these problems is asynchronous REST. Asynchronous REST works by separating request and real response. Here's an example, let's consider the following simple async REST broker:

This article contains the materials, examples, exercises to learn the basic concepts of IAM.

You have all resources available on this git : https://github.com/grongierisc/iam-training.

Solutions are in training branch.

Overview

Encryption of sensitive data becomes more and more important for applications. For example patient names, SSN, address-data or credit card-numbers etc..

Cache supports different flavors of encryption. Block-level database encryption and data-element encryption. The block-level database encryption protects an entire database. The decryption/encryption is done when a block is written/read to or from the database and has very little impact on the performance.

With data-element encryption only certain data-fields are encrypted. Fields that contain sensitive data like patient data or credit-card numbers. Data-element encryption is also useful if a re-encryption is required periodically. With data-element encryption it is the responsibility of the application to encrypt/decrypt the data.

Both encryption methods leverage the managed key encryption infrastructure of Caché.

The following article describes a sample use-case where data-element encryption is used to encrypt person data.

But what if you have hundreds of thousands of records with an encrypted datafield and you have the need to search that field? Decryption of the field-values prior to the search is not an option. What about indices?

This article describes a possible solution and develops step-by-step a small example how you can use SQL and indices to search encrypted fields.

Developing a Full-Stack JavaScript web app with Caché requires you to bring together the right building blocks. In this third part of this article series I will show how to link our React app to our three back-ends we created in part 2.