Wxr File Splitter Download
Polo Barlow
The areas.list file is the list of bounding boxes that were calculated. If you want you can use this on a subsequent call the the splitter using the --split-file option to use exactly the same areas as last time. This might be useful if you produce a map regularly and want to keep the tile areas the same from month to month. It is also useful to avoid the time it takes to regenerate the file each time (currently about a third of the overall time taken to perform the split). Of course if the map grows enough that one of the tiles overflows you will have to re-calculate the areas again.
You can also use a gzip'ed or bz2'ed compressed .osm file as the input file. Note that this can slow down the splitter considerably (particularly true for bz2) because decompressing the .osm file can take quite a lot of CPU power. If you are likely to be processing a file several times you're probably better off converting the file to one of the binary formats pbf or o5m. The o5m format is faster to read, but requires more space on the disk.
If your machine has less than 1GB free memory (eg. a netbook), you can still use splitter, but you might have to be patient if you use the parameter --keep-complete and want to split a file like germany.osm.pbf or a larger one. If needed, reduce the number of parallel processed areas to 50 with the max-areas parameter. You have to use --keep-complete=false when splitting an area like Europe.
You may have to get all info from panes (like objects on it) and splitters, then delete the splitters, create new splitters in correct style, put all objects on the correct pane. I'd opt out. It won't be fun. It might not even be possible...
Sets a reference to the AggregationStrategy to be used to assemble the replies from the split messages, into a single outgoing message from the Splitter. By default Camel will use the original incoming message to the splitter (leave it unchanged). You can also use a POJO as the AggregationStrategy.
When in streaming mode, then the splitter splits the original message on-demand, and each split message is processed one by one. This reduces memory usage as the splitter do not split all the messages first, but then we do not know the total size, and therefore the org.apache.camel.Exchange#SPLIT_SIZE is empty. In non-streaming mode (default) the splitter will split each message first, to know the total size, and then process each message one by one. This requires to keep all the split messages in memory and therefore requires more memory. The total size is provided in the org.apache.camel.Exchange#SPLIT_SIZE header. The streaming mode also affects the aggregation behavior. If enabled then Camel will process replies out-of-order, e.g. in the order they come back. If disabled, Camel will process replies in the same order as the messages was split.
Will now stop further processing if an exception or failure occurred during processing of an org.apache.camel.Exchange and the caused exception will be thrown. Will also stop if processing the exchange failed (has a fault message) or an exception was thrown and handled by the error handler (such as using onException). In all situations the splitter will stop further processing. This is the same behavior as in pipeline, which is used by the routing engine. The default behavior is to not stop but continue processing till the end.
When parallel processing is enabled, then the Camel routing engin will continue processing using last used thread from the parallel thread pool. However, if you want to use the original thread that called the splitter, then make sure to enable the synchronous option as well.
And our custom AggregationStrategy that is responsible for holding the in progress aggregated message that after the splitter is ended will be sent to the buildCombinedResponse method for final processing before the combined response can be returned to the waiting caller.
Very pleased with my Split-Fire firewood splitter purchase to date. There was a small hiccup within the first couple hours of use but the team at Split-Fire had that sorted in short time. Since then I have run a decent amount of wood through it and it has performed flawlessly. Thanks again for great service and product!
The Tallysman TW164 is a professional-grade full GNSS band signal splitter that connects one antenna to four receivers, and supports GPS/QZSS-L1/L2/L5, QZSS-L6, GLONASS-G1/G2/G3, BeiDou-B1/B2/B2a/B3, Galileo-E1/E5a/E5b/E6, NavIC-L5, and L-band correction services.
The design of first-generation GNSS signal splitters suffered from a single point of failure: only one attached receiver powered the splitter and the antenna. If this receiver failed or was unplugged, all attached receivers also failed.
The TW164 offers the best in-class performance in terms of noise figure, isolation, and linearity. In addition, it is packaged in a corrosion-protected housing made of military-grade aluminum (6061-T6), which is robust, compact, and lightweight. The splitter has also passed the IP67 water ingression test.
This is a military qualified MS14 GPS splitter with one-input and four-outputs. It typically finds application where an input from an active GPS roof antenna is split evenly between four receiving GPS units.
The MS14 can be configured to pass DC from an RF output (J2) to the antenna input port (J1) in order to power an active GPS antenna on that port. The remaining RF outputs (J3, J4, and J5) would feature a 200 Ohm DC load to simulate an antenna DC current draw for any receiver connected to that port.
Alternatively, the MS14 can be configured with a MIL-STD-704 compliant 28 VDC Power Supply that will power the active GPS antenna connected to J1.
A window splitter is a moveable separator between two sections, or panes, of a window that enables users to change the relative size of the panes. A Window Splitter can be either variable or fixed. A fixed splitter toggles between two positions whereas a variable splitter can be adjusted to any position within an allowed range.
A window splitter has a value that represents the size of one of the panes, which, in this pattern, is called the primary pane. When the splitter has its minimum value, the primary pane has its smallest size and the secondary pane has its largest size. The splitter also has an accessible name that matches the name of the primary pane.
For example, consider a book reading application with a primary pane for the table of contents and a secondary pane that displays content from a section of the book. The two panes are divided by a vertical splitter labelled "Table of Contents". When the table of contents pane has its maximum size, the splitter has a value of 100, and when the table of contents is completely collapsed, the splitter has a value of 0.
Shifting gears, there are 3 "obviously named" attachments to this article. One is a fully documented stand-alone test script, one is a 5 sheet Excel spreadsheet with a performance chart on each sheet, and one is a zipped file which contains copies of the new VARCHAR(8000) and NVARCHAR(4000) splitters that I think you'll like.
Most folks know by now, that a "Tally Table" (or cteTally, which is a "table-less" version of the Tally Table) based CSV Splitter absolutely screams performance-wise beating all other "T-SQL Only" split methods quite handily. Here's a 1,000 row performance-curve chart of a cteTally splitter pitted against several other splitters. Each line, of course, represents a different type of splitter as indicated in the chart legend.
Most folks also know by now (it's a very common complaint, actually), that Tally Table and cteTally (which I'll include in the term "Tally Table" from here on because it's easier to say) splitters are only good for relatively short strings. The chart above shows performance curves only for a very limited 1 to 64 randomly sized elements (string values located between delimiters in a string) of 10 to 20 characters each. That range of the number of elements is actually pretty small compared to some requirements for splitting. Notice that the performance curve for the Tally Table is starting to look a little strange. It looks like it might be starting to curve up (slow down) a bit. What happens if we try to split strings with more than just 64 elements? Let's have a look at an expanded performance chart and see:
Yowch! It's true! The Tally Table splitter has a HUGE performance problem when more elements are involved and the overall length of the string has increased. Again, that big, fat Red line is the performance curve of the current "state-of-the-art" Tally Table (as an inline CTE) splitter and it's not nearly as linear as the others clearly are. The Tally Table splitter starts out by blowing the proverbial doors off all the standard collection of "T-SQL Only" splitters but then something strange begins to happen as the number of elements increase, which also means that the overall length of the string is increasing.
As you can see in the chart above, the Tally Table splitter begins to falter at about 125 random length elements of 10 to 20 characters each (about 2,000 characters including the delimiters). At 210 elements (about 3,360 characters including the delimiter), the Recursive CTE (rCTE), XML, and the Tally Table splitters are neck-and-neck. At 290 elements (about 4,640 characters including the delimiters), the Tally Table ties with two different types of While Loop splitters. Finally, stretching out to 480 elements (about 7,680 characters including the delimiters), the once proud Tally Table splitter is a sore loser even to the (gasp!) WHILE loop methods.
In this article, we'll first learn that there are really only two basic types of delimited string splitters in T-SQL and how they work. Up next, we'll learn a bit more about why Tally Table and cteTally splitters have such performance problems with longer strings and wider elements. Then, we'll learn how to solve those problems.
As stated in the introduction, there are really only two basic types of delimited string splitters regardless of whether you're using some form of procedural code or set-based code to write the splitter. It's important to understand how they work because, without such an understanding, you might end up like me when I was trying to figure all of this out; Sitting in the corner with my favorite "binky" (a small and very comfortable quilt from childhood), knees withdrawn into a near fetal position facing away from the light, twiddling my hair with one hand and sucking on a beer popsicle with the other whilst uttering whiny little unintelligible mutters about why I couldn't solve the performance problem of Tally Table splitters. ? And, NO, Steve Jones, you may NOT have a picture of that!
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