iextractor | Automate extraction from iOS firmware files
kandi X-RAY | iextractor Summary
kandi X-RAY | iextractor Summary
iExtractor is a collection of tools and scripts to automate data extraction from iOS firmware files (i.e. IPSW files). It runs on macOS and partially on Linux (certain tools and features only work on macOS). IPSW (iPhone Software) files are provided publicly by Apple for OTA (over-the-air) updates for devices running iOS. ipsw.me provides links to IPSW files by device and iOS version. Similar information is on The iPhone Wiki. IPSW files are ZIP files packing the filesystem, kernel image and other files. The filesystem image and kernel image files for iOS <= 9 are encrypted; the firmware keys for most of these files are provided by the community on The iPhone Wiki. In the command output below 058-25512-331.dmg (the largest file) is the filesystem image file and kernelcache.release.n41 is the kernel image file or the kernelcache.
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QUESTION
Background:
I am working with an organization that has an ever-growing collection of data types that they need to extract data from. I have no ability to change these data types. Some are machine-generated from XML files provided by other organizations; some are controlled by intransigent internal dev teams; and some are so old that no one is willing to change them in any way for fear that it will destabilize the entire Earth and cause it to crash into the sun. These classes don't share any common interface, and don't derive from any common type other than object
. A few sample classes are given below for illustration purposes:
ANSWER
Answered 2020-Apr-14 at 13:49The following snippet will create the concrete instance of Extractor
class and dynamically invokes a method of this instance
QUESTION
I have a big blob storage full of log files organized according to their identifiers at a number of levels: repository, branch, build number, build step number.
These are JSON files that contain an array of objects, each object has a timestamp
and an entry
value. I've already implemented a custom extractor (extending IExtractor
) that takes an input stream and produces a number of plain-text lines.
Initial load
Now I am trying to load all of that data to ADL Store. I created a query that looks similar to this:
...ANSWER
Answered 2017-Jun-23 at 06:50For your first question: Sounds like your FileSet pattern is generating a very large number of input files. To deal with that you may want to try the FileSets v2 preview which is documented under U-SQL Preview Features section in: https://github.com/Azure/AzureDataLake/blob/master/docs/Release_Notes/2017/2017_04_24/USQL_Release_Notes_2017_04_24.md
Input File Set scales orders of magnitudes better (opt-in statement is now provided)
Previously, U-SQL's file set pattern on EXTRACT expressions ran into compile time time-outs around 800 to 5000 files.
U-SQL's file set pattern now scales to many more files and generates more efficient plans.
For example, a U-SQL script querying over 2500 files in our telemetry system previously took over 10 minutes to compile now compiles in 1 minute and the script now executes in 9 minutes instead of over 35 minutes using a lot less AUs. We also have compiled scripts that access 30'000 files.
The preview feature can be turned on by adding the following statement to your script:
SET @@FeaturePreviews = "FileSetV2Dot5:on";
If you wanted to generate multiple extract statements based on partitions of your filepaths, you'd have to do it with some external code that generates one or more U-SQL scripts.
I don't have a good answer to your second question so I will get a colleague to respond. Hopefully the first part can get you unblocked for now.
QUESTION
I’m implementing a custom U-SQL Extractor for our internal file format (binary serialization). It works well in the "Atomic" mode:
...ANSWER
Answered 2017-Mar-13 at 17:59The file is indeed split into chunks (I think it is 1 GB at the moment, but the exact value is implementation defined and may change for performance reasons).
If the file is indeed row delimited, and assuming your raw input data for the row is less than 4MB, you can use the input.Split() function inside your UDO to do the splitting into rows. The call will automatically handle the case if the raw input data spans the chunk boundary (assuming it is less than 4MB).
Here is an example:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install iextractor
vfdecrypt cd tools/vfdecrypt/ make
lzssdec cd tools/lzssdec/ make
dsc_extractor cd tools/dyld/ make
xpwn cd tools/xpwn/ mkdir builddir cd builddir/ cmake .. make Use builddir/ for the folder name as it is hardcoded inside scripts.
sandblaster dependencies (only available on macOS): cd tools/sandblaster git submodule update --init tools/sandbox_toolkit # while in tools/sandblaster/ cd tools/sandbox_toolkit/extract_sbops make # while in tools/sandblaster/ cd tools/sandbox_toolkit/extract_sbprofiles make
Before running iExtractor scripts you need to create a config file in the root of the repository. You can make a copy of the config.sample file and update that:. In the config.sample file downloaded and extracted data is stored in subfolders in the current directory (STORE=.). You can update the STORE variable to a different folder where you want the data stored.
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