r3 | reduce engine written in python using redis | Map library

Consider building a list of data frames then rbind once outside the loop:

Here I'm wondering about the line [in s_client]
New, TLSv1/SSLv3, Cipher is ECDHE-RSA-AES256-GCM-SHA384

You're apparently using OpenSSL 1.0.2, where that's a basically useless relic. Back in the days when OpenSSL supported SSLv2 (mostly until 2010, although almost no one used it much after 2000), the ciphersuite values used for SSLv3 and up (including all TLS, but before 2014 OpenSSL didn't implement higher than TLS1.0) were structured differently than those used for SSLv2, so it was important to qualify the ciphersuite by the 'universe' it existed in. It has almost nothing to do with the protocol version actually used, which appears later in the session-param decode:

You can save the old index, then perform BOW and then put it back:

You can use dictionary, with keys "r1", "r2", etc. For example:

The reason the first query is so much faster is it went parallel. This means the cardinality estimator knew enough about the data it had to handle, and the query was large enough to tip the threshold for parallel execution. Then, the engine passed chunks of data for different processors to handle individually, then report back and repartition the streams.

With the value as a variable, it effectively becomes a scalar function evaluation, and a query cannot go parallel with a scalar function, because the value has to determined before the cardinality estimator can figure out what to do with it. Therefore, it runs in a single thread, and is slower.

Some sort of looping mechanism might help. Create the included indexes to assist the engine in handling this request. You can probably find a better looping mechanism, since you are familiar with the identity ranges you care about, but this should get you in the right direction. Adjust for your needs.

With a loop like this, it commits the changes with each loop, so you aren't locking the table indefinitely.

"Fold" has two related but distinct meanings in common parlance.

1. Fold as in Foldable. Viewing the datatype as a container, Foldable gives you access to the container's elements while throwing away any information about the shape of the container itself. (This is also the sense in which lens's Fold uses the term.) Not every datatype is Foldable — only those which can be viewed as a container.
2. "Fold" can also mean "catamorphism", which is a technique for writing higher-order functions which reduce a structure to a summary value. Every datatype has a corresponding catamorphism, but the signature of the catamorphism depends on the datatype.

The two meanings of "fold" happen to coincide when the datatype you're talking about is [] (which partly explains the confusion over the two meanings), but in general they don't. Your Tree happens to be a suitable candidate for either type of fold, and from your question I can't quite tell which one you're after, so I'll show you how to do both.

The easiest way to write an instance of Foldable is to turn on DeriveFoldable.

You should know that in a situation like this, an Arrayformula will not make the sheet faster than a dragdown Filter.

That said, here is the traditional way to solve these problems. Make a new tab. Place this formula in cell B2.

TextFormatter is definitely the way to go. What you need to build is the filter component for the TextFormatter. Basically, you can think of this as a keystroke processor (that handles mouse actions as well), where all of the low-level stuff has been handled for you. You get a TextFormatter.Change object passed to you, and you can see how that change will impact the value in the field, and then modify it, suppress it, or let it pass through.

So all of the formatting happens instantly, right in the TextField as you type.

I built one to handle North American style phone numbers, because it's a little more interesting than the European style since it has brackets and dashes. But you can adapt it.

The approach I took was to strip all of the formatting characters out of the string, then reformat it from scratch each time a change was made. This seems easier than trying to fiddle with it character by character. The only tricky part was hitting over a "-" or ")", where I assumed that you'd want to delete the number in front of the special character. It might make more sense to just move the caret to the left of the special character:

We can convert to data.frame as