scd | Steam Controller Daemon | Video Game library

Thank you to Chuck Walbourn for pointing me to the DirectXTK templates.

After changing my Graphics class to match the template, the full screen on longer blurs.

Although I am not changing the backbuffer screen resolution It needs to be unchanged so that the low resolution is stretched to fit the window. If I change the backbuffer it is difficult to see the game because it is then rendered so small.

It appears the reason the fullscreen mode is not blurred when using the template is because it is actually borderless windowed mode and not exclusive fullscreen.

You should add package-info.java file to your package with FileTransmissionResponse.java class and define xml schema.

After going through several trail and errors we landed on the materialized view for this query. The number of rows the query was scanning was almost 500k+ and no indexes and partitioning was helping. We tweaked the above query to create a Materialized view and then doing a select on top of it. We are now at 96ms. The generalized materialized view for the query in this question is shown below.

Typically no unfortunately (although you could possibly fake it using dataset partitions, dataflows or programmatically adding records to what's called a "push datasets" - and one of these would be easy nor stable). Power BI assumes that all data will be purged on a full refresh.

I now found out that I need to make my eigenvector to have real float32 type.

So I change my eigenvector line from eigenvecs = eigenvecs[:, 1:] to eigenvecs = eigenvecs[:, 1:].real.astype(np.float32).

This should work: df[~df["platform"].isin(n)] This will show the data frame masked where rows don't contain anything in list n

These are the changes that I did to fix the code. I passed the CartID to the code behind

Just trigger the something function from the clock function. Then it will run every second. Like this:

This is obviously complicated by the fact that the same "value" can repeat in multiple groups - so you can't just use straightforward MIN/MAX functions. You could probably code this in a javascript stored proc but I thought I'd try and find a solution in (almost) pure SQL.

The challenge is to try and create a "group" every time the value changes - as then you can do a simple MIN/MAX on the dates within the group. The way I have (hopefully!) solved this is as follows:

1. Create a CTE where a calculated field is set to the next value in a sequence whenever the value of the current row is different from the value in the previous row; where there is no difference then the field is set to null - this is important due to the way the LAG function in the next CTE handles NULLs
2. Create a 2nd CTE where a calculated grouping column is set to last non-null value in the calculated column created in the previous column - using the LAG function set to ignore nulls
3. From the 2nd CTE, query the min and max date values grouping by the key, value and grouping columns

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