Disable case sensitive mac os x

Found an awesome GIT tip for OSX users which are having problems with case- sensitivity and renaming of files. The issue occurs when you.
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Partition, subpartition, column, index, stored routine, event, and resource group names are not case-sensitive on any platform, nor are column aliases.

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However, names of logfile groups are case-sensitive. This differs from standard SQL. By default, table aliases are case-sensitive on Unix, but not so on Windows or macOS.

The following statement would not work on Unix, because it refers to the alias both as a and as A :. However, this same statement is permitted on Windows. To avoid problems caused by such differences, it is best to adopt a consistent convention, such as always creating and referring to databases and tables using lowercase names. This convention is recommended for maximum portability and ease of use.

This variable does not affect case sensitivity of trigger identifiers. On Windows, the default value is 1.

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macos - Mac - Convert from Case-Sensitive to Case-Insensitive File System - Super User

On macOS, the default value is 2. However, you may encounter difficulties if you want to transfer tables between platforms that differ in file system case sensitivity. To avoid data transfer problems arising from lettercase of database or table names, you have two options:.

Which format to use in MacOS Disk Utility

This preserves the lettercase of database and table names. The disadvantage of this is that you must ensure that your statements always refer to your database and table names with the correct lettercase on Windows. If you transfer your statements to Unix, where lettercase is significant, they do not work if the lettercase is incorrect.


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Object names may be considered duplicates if their uppercase forms are equal according to a binary collation. That is true for names of cursors, conditions, procedures, functions, savepoints, stored routine parameters, stored program local variables, and plugins. Paths that already exist in the VM and contain files are reserved by Docker and cannot be exported from macOS. See Performance tuning for volume mounts shared filesystems to learn about new configuration options available with the Docker Initially, any containerized process that requests ownership metadata of an object is told that its uid and gid own the object.

When any containerized process changes the ownership of a shared file system object, such as by using the chown command, the new ownership information is persisted in the com.

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Subsequent requests for ownership metadata return the previously set values. Ownership-based permissions are only enforced at the macOS file system level with all accessing processes behaving as the user running Docker. If this attempt fails, the object appears to be owned by the process accessing it until the extended attribute is readable again.

Most inotify events are supported in bind mounts, and likely dnotify and fanotify though they have not been tested are also supported. This means that file system events from macOS are sent into containers and trigger any listening processes there. Some events may be delivered multiple times.

These limitations do not apply to events between containers, only to those events originating in macOS. The macOS mount structure is not visible in the shared volume, but volume contents are visible. Volume contents appear in the same file system as the rest of the shared file system. Unmount events are not supported. Mount export support is planned but is still under development. Symlinks are shared unmodified. This may cause issues when symlinks contain paths that rely on the default case-insensitivity of the default macOS file system.

Symlinks, hardlinks, socket files, named pipes, regular files, and directories are supported. Socket files and named pipes only transmit between containers and between macOS processes -- no transmission across the hypervisor is supported, yet. Character and block device files are not supported. With regard to reported performance issues GitHub issue File access in mounted volumes extremely slow , and a similar thread on Docker Desktop for Mac forums on topic: File access in mounted volumes extremely slow , this topic provides an explanation of the issues, recent progress in addressing them, how the community can help us, and what you can expect in the future.

This explanation derives from a post about understanding performance by David Sheets dsheets on the Docker development team to the forum topic just mentioned. We want to surface it in the documentation for wider reach. Perhaps the most important thing to understand is that shared file system performance is multi-dimensional. This means that, depending on your workload, you may experience exceptional, adequate, or poor performance with osxfs , the file system server in Docker Desktop for Mac.

File system APIs are very wide message types with many intricate semantics involving on-disk state, in-memory cache state, and concurrent access by multiple processes. Latency is the time it takes for a file system call to complete.

Can no longer use 4.18 on OSX with case-sensitive filesystem

For instance, the time between a thread issuing write in a container and resuming with the number of bytes written. For workloads which demand many sequential roundtrips, this results in significant observable slowdown. Reducing the latency requires shortening the data path from a Linux system call to macOS and back again.

This requires tuning each component in the data path in turn -- some of which require significant engineering effort. This is typical of performance engineering, which requires significant effort to analyze slowdowns and develop optimized components. A second approach to improving performance is to reduce the number of roundtrips by caching data. Recent versions of Docker Desktop for Mac Further caching developments, including support for write caching, are planned. A detailed description of the behavior in various caching configurations is available. We continue to actively work on increasing caching and on reducing the file system data path latency.

This requires significant analysis of file system traces and speculative development of system improvements to try to address specific performance issues. Perhaps surprisingly, application workload can have a huge effect on performance. As an example, here are two different use cases contributed on the forum topic and how their performance differs and suffers due to latency, caching, and coherence:. With caching enabled the performance increases around 3.

However, even this is not sufficient for the first time rake is run on a shared directory.