Have some free text fields in your application that you wish you could search efficiently? Tried using some methods before but found out that they just cannot match the performance needs of your customers? Do I have one weird trick that will solve all your problems? Don’t you already know!? All I do is bring great solutions to your performance pitfalls!

As usual, if you want the TL;DR (too long; didn’t read) version, skip to the end. Just know you are hurting my feelings.

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Date range queries going too slow for you? SQL Performance got you down? I have one weird trick that might just help you out! (SQL Developers hate this!)*

If you have a class that records timestamps when the data is added, then that data will be in sequence with your IDKEY values - that is, TimeStamp1 < TimeStamp2 if and only if ID1 < ID2 for all IDs and TimeStamp values in table - then you can use this knowledge to increase performance for queries against TimeStamp ranges. Consider the following table:

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Python has become the most used programming language in the world (source: https://www.tiobe.com/tiobe-index/) and SQL continues to lead the way as a database language. Wouldn't it be great for Python and SQL to work together to deliver new functionality that SQL alone cannot? After all, Python has more than 380,000 published libraries (source: https://pypi.org/) with very interesting capabilities to extend your SQL queries within Python.

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Article
Eduard Lebedyuk · Feb 5, 2016 11m read
Class Queries in InterSystems IRIS

Class Queries in InterSystems IRIS (and Cache, Ensemble, HealthShare) is a useful tool that separates SQL queries from Object Script code. Basically, it works like this: suppose that you want to use the same SQL query with different arguments in several different places.In this case you can avoid code duplication by declaring the query body as a class query and then calling this query by name. This approach is also convenient for custom queries, in which the task of obtaining the next row is defined by a developer. Sounds interesting? Then read on!

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As you know in Caché / IRIS you have the possibility to define a property as Multidimensional as documented here:
https://docs.intersystems.com/iris20201/csp/docbook/DocBook.UI.Page.cls?KEY=GOBJ_proplit#GOBJ_proplit_multidim
and the explanation of how to use it
https://docs.intersystems.com/iris20201/csp/docbook/Doc.View.cls?KEY=GOBJ_proplit#GOBJ_proplit_multidim_values

Though the access is quite comfortable (in traditional COS sense) there are 2 main restrictions that hurt:

#1) It is not saved to disk unless your application includes code to save it specifically.
#2) It cannot be stored in or exposed through SQL tables
there are some more
I'll show how to overcome these limits

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InterSystems IRIS 2020.1 brings a broad set of improved and new capabilities to help build important applications. In addition to the many significant performance improvements accrued through 2019.1 and 2020.1, we are introducing one of our biggest changes in recent SQL history: the Universal Query Cache. This article provides more context on its impact to SQL-based applications at a technical level.

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Last week, we announced the InterSystems IRIS Data Platform, our new and comprehensive platform for all your data endeavours, whether transactional, analytics or both. We've included many of the features our customers know and loved from Caché and Ensemble, but in this article we'll shed a little more light on one of the new capabilities of the platform: SQL Sharding, a powerful new feature in our scalability story.

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Introduction

The field test of Caché 2016.2 has been available for quite some time and I would like to focus on one of the substantial features that is new in this version: the document data model. This model is a natural addition to the multiple ways we support for handling data including Objects, Tables and Multidimensional arrays. It makes the platform more flexible and suitable for even more use cases.

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Article
Benjamin De Boe · Feb 13 4m read
When to use Columnar Storage

With InterSystems IRIS 2022.2, we introduced Columnar Storage as a new option for persisting your IRIS SQL tables that can boost your analytical queries by an order of magnitude. The capability is marked as experimental in 2022.2 and 2022.3, but will "graduate" to a fully supported production capability in the upcoming 2023.1 release.

The product documentation and this introductory video, already describe the differences between row storage, still the default on IRIS and used throughout our customer base, and columnar table storage and provide high-level guidance on choosing the appropriate storage layout for your use case. In this article, we'll elaborate on this subject and share some recommendations based on industry-practice modelling principles, internal testing, and feedback from Early Access Program participants.

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The 2021.2 release of the InterSystems IRIS Data Platform includes many exciting new features for fast, flexible and secure development of your mission-critical applications. Embedded Python definitely takes the limelight (and for good reason!), but in SQL we've also made a massive step forward towards a more adaptive engine that gathers detailed statistical information about your table data and exploits it to deliver the best query plans. In this brief series of articles, we'll take a closer at three elements that are new in 2021.2 and work together towards this goal, starting with Run Time Plan Choice.

It's hard to figure out the right order to talk about these (you can't imagine how often I've reshuffled them in writing this article!) because they fit together in such a nice way. As such, feel free to go on a limb and read these in random order smiley.

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Announcement
Mike Kadow · Jul 9, 2018
Caché SQL Queries

I have finished my 4th book about Caché and MUMPS. This will probably be my last.

I am deeply grateful and humbled for all the help I have received from this group and the WW Response Center.

You all have something very special going here.

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Question
Robert Cemper · Apr 26, 2020
Materialized Views

A VIEW in SQL is basically a prepared SQL statement.
It has to be executed and assembled like any other SQL query.
MATERIALIZED VIEW means that the content is collected before hands and can be retrieved rather fast.
I saw the concept first with my favorite competitor named O* and they made a lot of noise about it.

{ favorite: because I could win every benchmark against them devil }

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Article
Vicky Li · Nov 14, 2016 14m read
Mastering the JDBC SQL Gateway

As we all know, Caché is a great database that accomplishes lots of tasks within itself. However, what do you do when you need to access an external database? One way is to use the Caché SQL Gateway via JDBC. In this article, my goal is to answer the following questions to help you familiarize yourself with the technology and debug some common problems.

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The object and relational data models of the Caché database support three types of indexes, which are standard, bitmap, and bitslice. In addition to these three native types, developers can declare their own custom types of indexes and use them in any classes since version 2013.1. For example, iFind text indexes use that mechanism.

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Hi,

I'm doing a query in SQL and I need to sort my data by some non-repeated field.

Unfortunately, my data is grouped in a way that I cannot guarantee that any column will not have repeated data, so one solution would be to take the row number.

Also, the Cache is not accepting Row_Number () in my querry and I would like to know if there is another solution to return line numbers or some way to add this function to the Cache.

Best regards.

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Announcement
Stefan Wittmann · Aug 25, 2016
JSON changes in Caché 2016.2

As Bill has mentioned earlier in his post, we have carefully reviewed the JSON capabilities and made some adjustments to ensure they deliver the best benefit to you. In this post, I am going to describe the modifications in more detail and provide guidance for you to understand the implication for your code base.

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