anyhow | Flexible concrete Error type built on std : :error : :Error | Architecture library

You're right. You need to use HRTB. The syntax is like:

Consider this approach, loosely inspired by my earlier post about lines from points

To make it more reproducible I am using the well known & much loved North Carolina shapefile that ships with {sf} and a data frame of three semi-random NC cities.

What the code does is:

• iterates via for cycle over the dataframe of cities
• creates a line starting in each city ("observation") and ending on South Pole
• intersects the line with dissolved North Carolina
• blasts the intersection to individual linestrings
• selects the linestring that passes within 1 meter of origin
• calculates the lenght via sf::st_lenghth()
• saves the the result as a {sf} data frame called res (short for result :)

I have included the actual line in the final object to make the result more clear, but you can choose to omit it.

If you switch to

firebaser here

Firebase Extensions normally declare their triggers in the extension.yaml file, instead of in the code itself. Therefore, in order to emulate an extension in this way, you'd need to move the triggers over to the code.

For your specific example of the 'worker' function, the extension declares what document to listen to here, so we'll copy the document over to the code:

There is no such thing as index for linked lists. Linked lists are not arrays.

If you are trying to get to the next value after a bunch of %{day: "mon"}, you might want to reduce

One of the issues is that partition is an overloaded term in Spark world and you're looking at 2 different kind of partitions:

• your dataset is organized as a Hive-partitioned table, where each partition is a separate directory named with = that may contain many data files inside. This is only useful for dynamically pruning the set of input files to read and has no effect on the actual RDD processing

• when Spark loads your data and creates a DataFrame/RDD, this RDD is organized in splits that can be processed in parallel and that are also called partitions.

df.rdd.getNumPartitions() returns the number of splits in your data and that is completely unrelated to your input table partitioning. It's determined by a number of config options but is mostly driven by 3 factors:

• computing parallelism: spark.default.parallelism in particular is the reason why you have 2 partitions in your RDD even though you don't have enough data to fill the first
• input size: spark will try to not create partitions bigger than spark.sql.files.maxPartitionBytes and thus may split a single multi-gigabyte parquet file into many partitions)
• shuffling: any operation that need to reorganize data for correct behavior (for example join or groupBy) will repartition your RDD with a new strategy and you will end up with many more partitions (governed by spark.sql.shuffle.partitions and AQE settings)

On the whole, you want to preserve this behavior since it's necessary for Spark to process your data in parallel and achieve good performance. When you use df.coalesce(1) you will coalesce your data into a single RDD partition but you will do your processing on a single core in which case simply doing your work in Pandas and/or Pyarrow would be much faster.

If what you want is to preserve the property on your output to have a single parquet file per Hive-partition attribute, you can use the following construct:

• As of PowerShell 7.2, output from external programs is invariably decoded as text before further processing, which means that raw (byte) output can neither be passed on via | nor captured with >. See this answer for details.

• PowerShell's > redirection operator is effectively an alias of Out-File, and its default character encoding therefore applies.

In Windows PowerShell, Out-File defaults to "Unicode" encoding, i.e. UTF-16LE:

• This encoding uses a BOM (byte-order mark), whose bytes, if interpreted individually as ANSI (Windows-1252) bytes, render as ÿþ), and it represents most characters as two-byte sequences,^[1] which in the case of most characters in the Windows-1252 character set (which itself is a superset of ASCII) means that the second byte in each sequence is a NUL (0x0 byte) - this is what you're seeing.

Fortunately, in PowerShell (Core) 7+, all file-processing cmdlets now consistently default to (BOM-less) UTF-8.

To use a different encoding, either call Out-File explicitly and use its -Encoding parameter, or - as you have done, and as is generally preferable for the sake of performance when dealing with data that already is text - use Set-Content.

^{[1] At least two bytes are needed per character; for characters outside the so-called BMP (Basic Multilingual Plane), a pair of two-byte sequences is needed.}

You could use expand.grid:

The computation of clicked_row and clicked_col is wrong. The problem is that if you click on the right side of the window, the result of mouseX // 160 may be 3.

The grid has 3 rows and 3 columns. The width is 550 and the height is 450. Compute clicked_row and clicked_col as follows: