Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://arrow.apache.org/docs/python/generated/pyarrow.MemoryPool.html below:

pyarrow.MemoryPool — Apache Arrow v20.0.0

class pyarrow.MemoryPool#

Bases: _Weakrefable

Base class for memory allocation.

Besides tracking its number of allocated bytes, a memory pool also takes care of the required 64-byte alignment for Arrow data.

__init__(*args, **kwargs)#

Methods

Attributes

backend_name#

The name of the backend used by this MemoryPool (e.g. “jemalloc”).

bytes_allocated(self)#

Return the number of bytes that are currently allocated from this memory pool.

max_memory(self)#

Return the peak memory allocation in this memory pool. This can be an approximate number in multi-threaded applications.

None is returned if the pool implementation doesn’t know how to compute this number.

num_allocations(self)#

Return the number of allocations or reallocations that were made using this memory pool.

print_stats(self)#

Print statistics about this memory pool.

The output format is implementation-specific. Not all memory pools implement this method.

release_unused(self)#

Attempt to return to the OS any memory being held onto by the pool.

This function should not be called except potentially for benchmarking or debugging as it could be expensive and detrimental to performance.

This is best effort and may not have any effect on some memory pools or in some situations (e.g. fragmentation).

total_bytes_allocated(self)#

Return the total number of bytes that have been allocated from this memory pool.

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4