New SQL Docs
We just launched a new sql documentation website: sqldock.com
to allow integration with Pulse / qStudio and docs more easily.
More updates on this integration will be announced shortly. 🙂
We just launched a new sql documentation website: sqldock.com
to allow integration with Pulse / qStudio and docs more easily.
More updates on this integration will be announced shortly. 🙂
Support for 30+ databases has now been added to both qStudio and Pulse.
Clickhouse, Redis, MongoDB, Timescale, DuckDB, TDEngine and the full list shown below are all now supported.
Pulse is being used successfully to deliver data apps including TCA, algo controls, trade blotters and various other financial analytics. Our users wanted to see all of their data in one place without the cost of duplication. Today we released support for 30+ databases.
“My market data travels over ZeroMQ, is cached in Reddit and stored into QuestDB. While static security data is in SQL server. With this change to Pulse I can view all my data easily in one place.” – Mark – Platform Lead at Crypto Algo Trading Firm.
In particular we have worked closely with chosen vendors to ensure compatibility.
A number of vendors have tested the system and documented setup on their own websites:
qStudio release 2.05 added:
Notice Also
qStudio is the number one code editor, server browser and development environment for kdb+.
Today we are launching Pulse, a real-time SQL visualization tool for almost any SQL database.
Within Pulse we have recreated almost all the functionality of qStudio in web form.
If you’ve ever wanted to:
You should consider using Pulse as a shared HTML5 based complement to qStudio..
As you can see below, pulse can be made to look almost the exact same as qStudio. It features the familiar configurable layout with a table/console/charting result panel that allows you to see your result in all formats at once.
Additionally you can
qStudio 1.45 Released, we have:
Some example charts:
Our standard time-series graph interpolates between points. When the data you are displaying is price points, it’s not really valid to always interpolate. If the price was 0.40 at 2pm then 0.46 at 3pm, that does not mean it could be interpreted as 0.43 at 2.30pm. Amazingly till now, sqlDashboards had no sensible way to show taht data. Now we do:
For comparison here is the same data as a time-series graph:
The step-plot is usable for time-series and numerical XY data series. The format is detailed on the usual chart format pages.
qStudio has added support for stacked bar charts:
The chart format for this is: The first string columns are used as category labels. Whatever numeric columns appear next are a separate series in the chart. Each row in the data becomes one stacked bar. The table for the data shown above for example is:
dt | LSE | BTS | NAS | ASE | NYQ | SES | TSE | HKG |
---|---|---|---|---|---|---|---|---|
2018-03-30 | 1047 | 2120 | 592 | 25 | 3660 | 303 | 225 | 383 |
2018-03-29 | 1148 | 2118 | 528 | 10 | 3656 | 541 | 215 | 303 |
2018-03-28 | 1201 | 2085 | 555 | 17 | 3644 | 302 | 290 | 339 |
2018-03-27 | 1206 | 2182 | 535 | 21 | 3604 | 235 | 299 | 319 |
2018-03-26 | 1239 | 2041 | 515 | 16 | 3549 | 251 | 234 | 363 |
2018-03-25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
2018-03-24 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
2018-03-23 | 1379 | 2115 | 595 | 29 | 3430 | 138 | 251 | 348 |
2018-03-22 | 1431 | 2179 | 517 | 25 | 3399 | 531 | 222 | 320 |
2018-03-21 | 1530 | 2032 | 558 | 29 | 3282 | 438 | 296 | 359 |
2018-03-20 | 1531 | 2134 | 520 | 23 | 3256 | 515 | 265 | 322 |
You may need to “kdb pivot” your original data to get it in the correct shape.
“The Financial Information eXchange (FIX) protocol is an electronic communications protocol initiated in 1992 for international real-time exchange of information related to the securities transactions and markets.”. You can see an example of a FIX message being parsed here.
What we care about is that an order goes through a lifecycle. From newly created to filled or removed. Anything that involves state-transitions or a lifecycle can be visualized as a graph. A graph depicts transitions from one state to another. Often SQL tables record every transition of that state. This can then be summarised into a count of the last state, giving something like the following:
From | To | label | cnt |
---|---|---|---|
PendingCancel | Calculated | Rejected | 50 |
PendingReplace | Calculated | Rejected | 10 |
PendingReplace | Calculated | Replaced | 40 |
Calculated | PendingReplace | PendingReplace | 50 |
Calculated | Filled | Trade | 9400 |
Calculated | Calculated | Trade | 5239 |
PendingCancel | Removed | Cancelled | 150 |
Calculated | PendingCancel | PendingCancel | 200 |
New | Calculated | Calculated | 9660 |
New | Removed | Rejected | 140 |
Created | Removed | Rejected | 300 |
Created | New | New | 9800 |
qStudio now automatically converts this result table to DOT format and if you have graphviz“>graphviz installed and on the PATH, will generate the following:
Note I did tweak the table a little to add styling like so:
update style:(`Filled`Removed!("color=green";"color=red")) To,label:(label,'" ",/:cnt) from currentFixStatus
The format is detailed again in our qStudio Chart Data Format page.
This is another even simpler example:
qStudio 1.43 Released. This:
Download it now.
kdb+ 3.5 had a significant number of changes:
The feature that most interests us right now is the Debugging functionality. If you are not familiar with how basic errors, exceptions and stack movement is handled in kdb see our first article on kdb debugging here. In this short post we will only look at the new stack trace functionality.
Now when you run a function that causes an error at the terminal you will get the stack trace. Here’s a simple example where the function f fails:
Whatever depth the error occurs at we get the full depth stack trace, showing every function that was called to get there using .Q.bt[]:
The good news is that this same functionality is availabe in qStudio 1.43. Give it a try: qStudio.
Note: the ability to show stack traces relies on qStudio wrapping every query you send to the server with its own code to perform some analysis and return those values. By default wrapping is on as seen in preferences. If you are accessing a kdb server ran by someone else you may have to turn wrapping off as that server may limit which queries are allowed. Unfortunately stack tracing those queries won’t be easily possible.
That’s just the basics, there are other new exposed functions and variables, such as .Q.trp – for trapping calls and accessing traces that we are going to look at in more detail in future.