R: Create a disk cache object

cache_disk {cachem} | R Documentation

## Create a disk cache object

### Description

A disk cache object is a key-value store that saves the values as files in a directory on disk. Objects can be stored and retrieved using the `get()` and `set()` methods. Objects are automatically pruned from the cache according to the parameters `max_size`, `max_age`, `max_n`, and `evict`.

### Usage

    cache_disk(
      dir = NULL,
      max_size = 1024 * 1024^2,
      max_age = Inf,
      max_n = Inf,
      evict = c("lru", "fifo"),
      destroy_on_finalize = FALSE,
      missing = key_missing(),
      prune_rate = 20,
      warn_ref_objects = FALSE,
      logfile = NULL
    )

### Arguments

`dir` | Directory to store files for the cache. If `NULL` (the default) it will create and use a temporary directory.
`max_size` | Maximum size of the cache, in bytes. If the cache exceeds this size, cached objects will be removed according to the value of the `evict`. Use `Inf` for no size limit. The default is 1 gigabyte.
`max_age` | Maximum age of files in cache before they are evicted, in seconds. Use `Inf` for no age limit.
`max_n` | Maximum number of objects in the cache. If the number of objects exceeds this value, then cached objects will be removed according to the value of `evict`. Use `Inf` for no limit of number of items.
`evict` | The eviction policy to use to decide which objects are removed when a cache pruning occurs. Currently, `"lru"` and `"fifo"` are supported.
`destroy_on_finalize` | If `TRUE`, then when the cache_disk object is garbage collected, the cache directory and all objects inside of it will be deleted from disk. If `FALSE` (the default), it will do nothing when finalized.
`missing` | A value to return when `get(key)` is called but the key is not present in the cache. The default is a `key_missing()` object. It is actually an expression that is evaluated each time there is a cache miss. See section Missing keys for more information.
`prune_rate` | How often to prune the cache. See section Cache Pruning for more information.
`warn_ref_objects` | Should a warning be emitted when a reference is stored in the cache? This can be useful because serializing and deserializing a reference object (such as environments and external pointers) can lead to unexpected behavior.
`logfile` | An optional filename or connection object to where logging information will be written. To log to the console, use `stderr()` or `stdout()`.

### Value

A disk caching object, with class `cache_disk`.

### Missing keys

The `missing` parameter controls what happens when `get()` is called with a key that is not in the cache (a cache miss). The default behavior is to return a `key_missing()` object. This is a sentinel value that indicates that the key was not present in the cache. You can test if the returned value represents a missing key by using the `is.key_missing()` function. You can also have `get()` return a different sentinel value, like `NULL`. If you want to throw an error on a cache miss, you can do so by providing an expression for `missing`, as in `missing = stop("Missing key")`.

When the cache is created, you can supply a value for `missing`, which sets the default value to be returned for missing values. It can also be overridden when `get()` is called, by supplying a `missing` argument. For example, if you use `cache$get("mykey", missing = NULL)`, it will return `NULL` if the key is not in the cache.

The `missing` parameter is actually an expression which is evaluated each time there is a cache miss. A quosure (from the rlang package) can be used.

If you use this, the code that calls `get()` should be wrapped with `tryCatch()` to gracefully handle missing keys.

### Cache pruning

Cache pruning occurs when `set()` is called, or it can be invoked manually by calling `prune()`.

The disk cache will throttle the pruning so that it does not happen on every call to `set()`, because the filesystem operations for checking the status of files can be slow. Instead, it will prune once in every `prune_rate` calls to `set()`, or if at least 5 seconds have elapsed since the last prune occurred, whichever is first.

When a pruning occurs, if there are any objects that are older than `max_age`, they will be removed.

The `max_size` and `max_n` parameters are applied to the cache as a whole, in contrast to `max_age`, which is applied to each object individually.

If the number of objects in the cache exceeds `max_n`, then objects will be removed from the cache according to the eviction policy, which is set with the `evict` parameter. Objects will be removed so that the number of items is `max_n`.

If the size of the objects in the cache exceeds `max_size`, then objects will be removed from the cache. Objects will be removed from the cache so that the total size remains under `max_size`. Note that the size is calculated using the size of the files, not the size of disk space used by the files — these two values can differ because of files are stored in blocks on disk. For example, if the block size is 4096 bytes, then a file that is one byte in size will take 4096 bytes on disk.

Another time that objects can be removed from the cache is when `get()` is called. If the target object is older than `max_age`, it will be removed and the cache will report it as a missing value.

### Eviction policies

If `max_n` or `max_size` are used, then objects will be removed from the cache according to an eviction policy. The available eviction policies are:

`"lru"`

  Least Recently Used. The least recently used objects will be removed. This uses the filesystem's mtime property. When "lru" is used, each `get()` is called, it will update the file's mtime using `Sys.setFileTime()`. Note that on some platforms, the resolution of `Sys.setFileTime()` may be low, one or two seconds.

`"fifo"`

  First-in-first-out. The oldest objects will be removed.

Both of these policies use files' mtime. Note that some filesystems (notably FAT) have poor mtime resolution. (atime is not used because support for atime is worse than mtime.)

### Sharing among multiple processes

The directory for a cache_disk can be shared among multiple R processes. To do this, each R process should have a cache_disk object that uses the same directory. Each cache_disk will do pruning independently of the others, so if they have different pruning parameters, then one cache_disk may remove cached objects before another cache_disk would do so.

Even though it is possible for multiple processes to share a cache_disk directory, this should not be done on networked file systems, because of slow performance of networked file systems can cause problems. If you need a high-performance shared cache, you can use one built on a database like Redis, SQLite, mySQL, or similar.

When multiple processes share a cache directory, there are some potential race conditions. For example, if your code calls `exists(key)` to check if an object is in the cache, and then call `get(key)`, the object may be removed from the cache in between those two calls, and `get(key)` will throw an error. Instead of calling the two functions, it is better to simply call `get(key)`, and check that the returned object is not a `key_missing()` object, using `is.key_missing()`. This effectively tests for existence and gets the object in one operation.

It is also possible for one processes to prune objects at the same time that another processes is trying to prune objects. If this happens, you may see a warning from `file.remove()` failing to remove a file that has already been deleted.

### Methods

A disk cache object has the following methods:

`get(key, missing)`

  Returns the value associated with `key`. If the key is not in the cache, then it evaluates the expression specified by `missing` and returns the value. If `missing` is specified here, then it will override the default that was set when the `cache_mem` object was created. See section Missing Keys for more information.

`set(key, value)`

  Stores the `key`-`value` pair in the cache.

`exists(key)`

  Returns `TRUE` if the cache contains the key, otherwise `FALSE`.

`size()`

  Returns the number of items currently in the cache.

`keys()`

  Returns a character vector of all keys currently in the cache.

`reset()`

  Clears all objects from the cache.

`destroy()`

  Clears all objects in the cache, and removes the cache directory from disk.

`prune()`

  Prunes the cache, using the parameters specified by `max_size`, `max_age`, `max_n`, and `evict`.

[Package cachem version 1.0.4 Index]