2 releases
0.1.16-alpha.0 | Apr 1, 2023 |
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0.1.12-alpha.0 | Jan 19, 2023 |
#5 in #compaction
519 downloads per month
Used in 66 crates
(via bitcoin-leveldb)
785KB
2K
SLoC
bitcoinleveldb-merger
This Rust crate is a direct translation from the C++ code of the Bitcoin Core system. The purpose of this crate is to provide functionality for merging sorted sequences, which is used in the LevelDB implementation of Bitcoin Core.
The main token in this crate is MergingIterator
,
which represents an iterator that merges multiple
sorted sequences into a single sorted
sequence. This iterator is used extensively in the
compaction process of LevelDB, where it is used to
merge multiple sorted SSTables into a single,
larger SSTable.
The MergingIterator
uses a Direction
parameter
to determine the order of iteration, either
forwards or backwards. The find_smallest
method
is used to find the smallest element in the merged
sequence that is greater than or equal to a given
key, which is used in seeking and skipping to
specific keys during iteration.
The complexity of the MergingIterator
depends on
the number of sequences being merged and the size
of those sequences. In the best case, where all
sequences have the same size, the time complexity
of merging n sequences of size m is O(nm log n),
while the worst case time complexity is O(nm log
nm).
In addition to time complexity, memory usage is
also an important metric when working with the
MergingIterator
. This is especially true in the
context of LevelDB compaction, where memory usage
can have a significant impact on performance. The
MergingIterator
is designed to use a small
amount of memory, proportional to the number of
input sequences being merged.
Overall, the MergingIterator
plays a critical
role in the compaction process of LevelDB and is
essential for maintaining the performance and
scalability of the database.
57> how does merging work in leveldb? how does it relate to compaction?
In LevelDB, merging refers to the process of merging multiple sorted SSTables into a single new SSTable. This process is performed during compaction, which is the process of combining and reducing the number of SSTables in the database.
When a new SSTable is created by compaction, it is made by merging multiple existing SSTables. The merging process is done in sorted order, and the resulting SSTable is sorted as well. This allows for efficient lookups using binary search.
The merging process is done using the
MergingIterator
class, which merges the contents
of multiple iterators in sorted order. This allows
for efficient merging of the SSTables, as the
contents of each SSTable is already sorted.
During the merging process, duplicate keys are handled by taking the newest value. If multiple SSTables contain the same key with different values, the value from the newest SSTable is used. This ensures that the resulting SSTable has the most up-to-date values for all keys.
Once the merging process is complete, the resulting SSTable is written to disk and the original SSTables are deleted. This reduces the total number of SSTables in the database, which helps to keep the size of the database manageable and reduce disk usage.
Dependencies
~90MB
~851K SLoC