Game Compressed
Leda Billock
Hey guys im having a problem opening folders I have downloaded from dropbox. I have since deleted it from dropbox (so cant try reloading the files). I have tried opening it 3 on different computers and im getting the same message. I tried using both windows 7 and windows 8.1
How big is this Zip file? Dropbox is known to have problems creating Zip files larger than 1GB or so. If you're using the built-in Zip support that Windows has, I would try a program like WinRAR, 7Zip or WinZip. Otherwise you may be out of luck.
Same here. Only, my compressed folders are from 1 to 116 MB. Not very large... I can't open any of the files when extracted, all broken. Pictures, txt files, pdf files, html files, mp3 files, nothing opens...
A strange thing happed to me... I've kept the broken zip archives - and they all work now, four weeks later. I changed my OS in the meantime (Mint to Ubuntu) but I don't know if that made any difference... I tried extracting one file at a time and all at once and it works, no problems whatsoever. Maybe you should try extracting one file at a time from the broken archive or something like that, or change the OS xD
Thanks so much for this answer. It worked for me and i have recovered hundreds of photos from my travels. If you are ever in nz let me know and i will buy you a beer!
Big shout out to mactorque who sorted it for me since i can hardly even turn a Mac on!
Its crazy that dropbox was not able to help with this issue.
Before you posted this I managed to get in touch with dropbox customer support which took a bit of hunting! However they repeatedly told me the fault was my doing, didn't believe what was happening to me and offered no solution!
Thanks so much!
We work with image, audio and video files and are concerned about fidelity. Are they compressed on upload to an update or the Files folder and uncompressed before (single file) download? I realize they are zipped when downloaded in a group.
Promoting energy and operational efficiency in compressed air systems for industry through information and training, leading end users to adopt efficient practices and technologies while leveraging collaborative cooperation among key stakeholders.
Many advertisers have spent the past several months operating on compressed schedules because they cannot do long-term planning, said Erik Requidan, the cofounder of the site monetization services consultancy Media Tradecraft.
I've been work ing on configuring compression using SSL communication between FW and Indexers for the last few hours, but was experiancing some isssues. I've since fixed the issue, but was hoping someone could answer a few questions. Reading through the How to docs, inputs.conf, and output.conf documenation I've notice what appears to discrepancies.
First: in Splunk 5.0.1 in the outputs.conf what is the difference between compressed and useClientSSLCompression? I though that useClientSSLCompression must be used when forwarding encrypted data to indexers; however I've noticed that while using this settings the indexer says it expected compression but forward is not configured. If I used compressed in my outputs.conf under my ssl stanza it works just fine. Is useClientSSLCompression depricated or a bug?
Second: In the documentation Configure_your_forwarders_to_use_your_certificates the compressed setting is used and in output.conf documentation under compressed it states *the following Applies to non-SSL forwarding only. For SSL useClientSSLCompression setting is use. Why is that?
The compressed attribute only matters if you are forwarding without SSL. It determines whether Splunk will or not perform "native" compression on a per-data chunk (UF, LWF) or per-event (HWF) basis for outgoing data. This must be enabled on both ends for things to work.
If you are forwarding with SSL, unless you explicitly set useClientSSLCompression to false, you will automatically benefit from SSL compression over the data stream. This is significantly more efficient than Splunk-native compression and should be favored in the case of bandwidth restrictions between forwarder and indexer.
So that not what I have been experiancing. If I use useClientSSLCompression on the forwarder Indexer closes the connection and the HWF say connection timed out. Though ifI use the compressed settings it works just fine. I'll post my conf shortly.
You can also configure SSL for other types of intra-Splunk communication, which is where the "useClientSSLCompression" attribute might be modified (it defaults to true and generally does not need to be modified). You can see more about the types of intra-Splunk configuration in the following topic:
The communication that I am talking about is in regards to outputs.conf for Splunk SSL encrypted communication. The other Intra-Splunk communications are controlled by the [sslConfig] stanza server.conf. What outher outputs in the outputs.conf file would use useClientSSLCompression?
Standlee Premium Western Forage Alfalfa Compressed Bales are made from compressed high-quality sun-cured forage and shrink-wrapped, making them easier to handle and store. Standlee Alfalfa hay bales are low in sugar, moderately high in protein, high in calories and digestible fiber to promote hind gut health.
Standlee Premium Western Forage Alfalfa Compressed Bales for horses and livestock can be an excellent source of calories for those who need help in gaining weight, or whose exercise demands require additional energy sources. Alfalfa hay offers an excellent source of protein, vitamin A, and calcium levels that can reduce the risk of stomach ulcers.
Weigh the amount of forage provided to each horse to ensure you are feeding the proper amount. This is especially important with baled and compressed forage since similar volumes of forage (a flake for example) vary in weight.
For lossless compression, the only way you can know how many times you can gain by recompressing a file is by trying. It's going to depend on the compression algorithm and the file you're compressing.
The reason that the second compression sometimes works is that a compression algorithm can't do omniscient perfect compression. There's a trade-off between the work it has to do and the time it takes to do it. Your file is being changed from all data to a combination of data about your data and the data itself.
We'll grow by one byte per iteration for a while, but it will actually get worse. One byte can only hold negative numbers to -128. We'll start growing by two bytes when the file surpasses 128 bytes in length. The growth will get still worse as the file gets bigger.
There's a headwind blowing against the compression program--the meta data. And also, for real compressors, the header tacked on to the beginning of the file. That means that eventually the file will start growing with each additional compression.
RLE is a starting point. If you want to learn more, look at LZ77 (which looks back into the file to find patterns) and LZ78 (which builds a dictionary). Compressors like zip often try multiple algorithms and use the best one.
Generally the limit is one compression. Some algorithms results in a higher compression ratio, and using a poor algorithm followed by a good algorithm will often result in improvements. But using the good algorithm in the first place is the proper thing to do.
If you have a large number of duplicate files, the zip format will zip each independently, and you can then zip the first zip file to remove duplicate zip information. Specifically, for 7 identical Excel files sized at 108kb, zipping them with 7-zip results in a 120kb archive. Zipping again results in an 18kb archive. Going past that you get diminishing returns.
Suppose we have a file N bits long, and we want to compress it losslessly, so that we can recover the original file. There are 2^N possible files N bits long, and so our compression algorithm has to change one of these files to one of 2^N possible others. However, we can't express 2^N different files in less than N bits.
This means that a compression algorithm can only compress certain files, and it actually has to lengthen some. This means that, on the average, compressing a random file can't shorten it, but might lengthen it.
Practical compression algorithms work because we don't usually use random files. Most of the files we use have some sort of structure or other properties, whether they're text or program executables or meaningful images. By using a good compression algorithm, we can dramatically shorten files of the types we normally use.
However, the compressed file is not one of those types. If the compression algorithm is good, most of the structure and redundancy have been squeezed out, and what's left looks pretty much like randomness.
No compression algorithm, as we've seen, can effectively compress a random file, and that applies to a random-looking file also. Therefore, trying to re-compress a compressed file won't shorten it significantly, and might well lengthen it some.
Corruption only happens when we're talking about lossy compression. For example, you can't necessarily recover an image precisely from a JPEG file. This means that a JPEG compressor can reliably shorten an image file, but only at the cost of not being able to recover it exactly. We're often willing to do this for images, but not for text, and particularly not executable files.
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