A lot of people are saying that once you get to the size where speed is actually a concern that HashSet<T> will always beat List<T>, but that depends on what you are doing. Let’s say you have a List<T> that will only ever have on average 5 items in it. Over a large number of cycles, if a single item … Read more
There is no difference. Reason: Books on-line says “COUNT ( { [ [ ALL | DISTINCT ] expression ] | * } )“ “1” is a non-null expression: so it’s the same as COUNT(*). The optimizer recognizes it for what it is: trivial. The same as EXISTS (SELECT * … or EXISTS (SELECT 1 … Example: Same IO, same plan, … Read more
The first way is easier to maintain. Each declaration is a single statement on a single line, so you can easily add, remove, and reorder the declarations. With the second way, it is annoying to remove the first or last declaration because they start from the var keyword and finish with the semicolon respectively. Every time you … Read more
Gcc 7.1 -O3 these are all identical, godbolt.org/z/a-hc1d – jterm Apr 25 at 3:27 Original answer: Did some digging. Below is an example program and the relevant assembly: Code: Assembly: This was compiled with -std=c++11 -O2. You can see that there is quite a lot more work for the return “”; statement and comparably little for return std::string and return {}; (these … Read more
hash_set is an extension that is not part of the C++ standard. Lookups should be O(1) rather than O(log n) for set, so it will be faster in most circumstances. Another difference will be seen when you iterate through the containers. set will deliver the contents in sorted order, while hash_set will be essentially random (Thanks Lou Franco). Edit: The C++11 … Read more
The difference is that apply lets you invoke the function with arguments as an array; call requires the parameters be listed explicitly. A useful mnemonic is “A for array and C for comma.” See MDN’s documentation on apply and call. Pseudo syntax: theFunction.apply(valueForThis, arrayOfArgs) theFunction.call(valueForThis, arg1, arg2, …) There is also, as of ES6, the possibility to spread the array for use with the call function, you can see the compatibilities here. Sample code:
I’ll do my best to explain it here on simple terms, but be warned that this topic takes my students a couple of months to finally grasp. You can find more information on the Chapter 2 of the Data Structures and Algorithms in Java book. There is no mechanical procedure that can be used to get the BigOh. As … Read more
It depends on what you are intending to do with it. Sets are significantly faster when it comes to determining if an object is present in the set (as in x in s), but are slower than lists when it comes to iterating over their contents. You can use the timeit module to see which is faster for … Read more
From the answer here, spark.sql.shuffle.partitions configures the number of partitions that are used when shuffling data for joins or aggregations. spark.default.parallelism is the default number of partitions in RDDs returned by transformations like join, reduceByKey, and parallelize when not set explicitly by the user. Note that spark.default.parallelism seems to only be working for raw RDD and is ignored when working with dataframes. If the task you are performing … Read more
guppy3 is quite simple to use. At some point in your code, you have to write the following: This gives you some output like this: You can also find out from where objects are referenced and get statistics about that, but somehow the docs on that are a bit sparse. There is a graphical browser as … Read more