A simple fast memory-first thread-safe (or goroutine-safe for Go) key-value embedded database that persist data on disk.
Project description
ckydb
A simple fast memory-first thread-safe (or goroutine-safe for Go) key-value embedded database that persists data on disk.
It is read as 'skydb' This the python implementation of ckydb
Quick Start
- Create a new project and activate your virtual environment
mkdir ckydb_example
cd ckydb_example
python3 -m venv env
source env/bin/activate
- Install ckydb
pip install ckydb
- Create a main.py file in the project folder and add the following code
if __name__ == '__main__':
import ckydb
keys = ["hey", "hi", "salut", "bonjour", "hola", "oi", "mulimuta"]
values = ["English", "English", "French", "French", "Spanish", "Portuguese", "Runyoro"]
with ckydb.connect("db", max_file_size_kb=(4 * 1024), vacuum_interval_sec=(5 * 60)) as db:
# setting the keys
for k, v in zip(keys, values):
db.set(k, v)
for i, k in enumerate(keys):
assert values[i] == db.get(k)
# updating keys
new_values = ["Jane", "John", "Jean", "Marie", "Santos", "Ronaldo", "Aliguma"]
for k, v in zip(keys, new_values):
db.set(k, v)
for i, k in enumerate(keys):
assert new_values[i] == db.get(k)
# deleting the keys
for k in keys[:2]:
db.delete(k)
for k, v in zip(keys[2:], new_values[2:]):
assert v == db.get(k)
errors = []
for k in keys[:2]:
try:
v = db.get(k)
except ckydb.exc.NotFoundError as exc:
errors.append(exc)
assert len(errors) == len(keys[:2])
# clear the database
errors.clear()
db.clear()
for k in keys:
try:
v = db.get(k)
except ckydb.exc.NotFoundError as exc:
errors.append(exc)
assert len(errors) == len(keys)
- Run the
main.py
module and observe the terminal
python main.py
How to Run Tests
- Clone the repo
git clone git@github.com:sopherapps/ckydb.git
- Enter the python implementation folder
cd ckydb/implementations/py_ckydb
- Create and activate the python 3.7+ virtual environment
python3 -m venv env
source env/bin/activate
- Run the test command
python -m unittest
Under the Hood
- Every key has a TIMESTAMP prefix, added to it on creation. This TIMESTAMPED key is the one used to store data in a sorted way for easy retrieval.
- The actual key known by user, however, is kept in the index. When ckydb is initialized, the index is loaded into
memory from the index file (a ".idx" file). The index is basically a map of
key: TIMESTAMPED-key
- The TIMESTAMPED-key and its value are stored first in a log file (a ".log" file). This current log file has an
in-memory copy we call
memtable
- When the current log file exceeds a predefined size (4MBs by default), it is converted to a sorted data file (a ".cky"
file) and
memtable
refreshed and a new log file created. - The names of each ".cky" or ".log" file are the timestamps when they were created. Do note that conversion of ".log" to "cky" just changes the file extension.
- There is always one ".log" file in the database folder. If on initialization, there is no ".log" file, a new one is created.
- There is an in-memory sorted list of ".cky" files called
data_files
that is kept updated everytime a ".log" file is converted into ".cky". - The name of the current log (
current_log_file
) file is also kept in memory, and updated when a new log file is created. - There is also a ".del" file that holds all the
key: TIMESTAMPED-key
pairs that have been marked for deletion. - At a predefined interval (5 minutes by default), a background task deletes the values from ".cky" and ".log" files
corresponding to the
key: TIMESTAMPED-key
pairs found in the ".del" file. Each deleted pair is then removed from the ".del" file. - On initial load, any keys in .del should have their values deleted in the corresponding ".log" or ".cky" files
Operations
-
On
ckydb.set(key, value)
:- the corresponding TIMESTAMPED key is searched for in the index
- if the key does not exist:
- a new TIMESTAMPED key is created and added to the index with its user-defined key
- the user-defined key and its TIMESTAMPED key are then added to the index file (".idx")
- this TIMESTAMPED key and its value are then added to
memtable
. - this TIMESTAMPED key and its value are then added to the current log file (".log")
- A check is made on the size of the log file. If the log file is bigger than the max size allowed,
it is rolled into a .cky file and a new log file created, and the
memtable
refreshed.
- if the key exists:
- its timestamp is extracted and compared to the current_log file to see if it is later than the current_log file
- if it is later or equal,
memtable
and the current log file are updated - else the timestamp is compared to cache's "start" and "stop" to see if it lies within the cache
- if it exists in the cache, then the cache data and its corresponding data file are updated
- else, the data file in which the timestamp exists is located within the data_files. This is done by finding
the two data files between which the timestamp exists when the list is sorted in ascending order. The file to
the left is the one containing the timestamp.
- the key-values from the data file are then extracted and they new key-value inserted
- the new data is then loaded into the cache
- the new data is also loaded into the data file
- If any error occurs on any of these steps, the preceding steps are reversed and the error returned/raised/thrown in the call
-
On
ckydb.delete(key)
:- Its
key: TIMESTAMPED-key
pair is removed from the in-memory index. - Its
key: TIMESTAMPED-key
pair is removed from the ".idx" file - Its
key: TIMESTAMPED-key
is added to the ".del" file - If any error occurs on any of these steps, the preceding steps are reversed and the error returned/raised/thrown in the call
- Its
-
On
ckydb.get(key)
:- the corresponding TIMESTAMPED key is searched for in the index
- if the key does not exist, a NotFoundError is thrown/raised/returned.
- if the key exists, its TIMESTAMP is extracted and checked if it is greater (later) than the name of the current log file.
- if this TIMESTAMP is later, its value is quickly got from
memtable
in memory. If for some crazy reason, it does not exist there, a CorruptedDataError is thrown/raised/returned. - If this TIMESTAMP is earlier than the name of the current log file, the TIMESTAMP is compared to the range in the
memory
cache
, if it falls there in, its value is got fromcache
. If the value is not found for some reason, a CorruptedDataError is thrown/raise/returned - Otherwise the ".cky" file whose name is earlier than the TIMESTAMP but whose neighbour to the right, in the
in-memory sorted
data_files
list, is later than TIMESTAMP is loaded into an in-memorycache
whose range is set to two ".cky" filenames between which it falls. - the value is then got from
cache
's data. If it is not found for some reason, a CorruptedDataError is thrown/raise/returned
-
On
ckydb.clear()
:memtable
is resetcache
is resetindex
in memory is resetdata_files
in memory is reset- all files in the database folder are deleted
- A new ".log" file is created
File formats
- The file format of the ".idx" index files is just "key<key_value_separator>TIMESTAMPED-key" separated by a unique token e.g. "{&*/%}" and a key_value_separator e.g. "[><?&(^#]"
goat[><?&(^#]1655304770518678-goat{&*/%}hen[><?&(^#]1655304670510698-hen{&*/%}pig[><?&(^#]1655304770534578-pig{&*/%}fish[><?&(^#]1655303775538278-fish$%#@*&^&
- The file format of the ".del" files is just "TIMESTAMPED-key" separated by a unique token e.g. "{&*/%}"
1655304770518678-goat{&*/%}1655304670510698-hen{&*/%}1655304770534578-pig{&*/%}1655303775538278-fish$%#@*&^&
- The file format of the ".log" and ".cky" files is just "TIMESTAMPED-key<key_value_separator>value" separated by a unique token e.g. "{&*/%}" and a key_value_separator like "[><?&(^#]"
1655304770518678-goat[><?&(^#]678 months{&*/%}1655304670510698-hen[><?&(^#]567 months{&*/%}1655304770534578-pig[><?&(^#]70 months{&*/%}1655303775538278-fish[><?&(^#]8990 months$%#@*&^&
Note: There is configuration that one can enable to escape the "token" in any user-defined key or value just to avoid weird errors. However, the escaping is expensive and it is thus turned off by default.
Ideas For Improvement
- Explicitly allow for multiple concurrent reads (e.g. don't lock at all on read)
- Explicitly allow for conditional multiple concurrent writes (e.g. lock on key, not on store)
- Distribute the database across different machines or nodes ( e.g. have multiple backend nodes, and let each node's timestamped key range be recorded on the master/main/gateway node(s). The gateway nodes themselves could be replicated. Clients read/update data through the gateway node)
Multiple Concurrent Reads, Single Writes at a time
- Have no lock on the main routine of
ckydb.get
.ckydb.get
has propsindex
,memtable
andcache
as its source of truth. - To avoid using a stale
cache
and yet also avoid data races betweenstore.set
andstore.get
, both, of old keys, we have acache_lock
lock. This lock is to be obtained by eitherstore.get
orstore.set
both for old keys - Have the same
mut_lock
lock on theckydb.delete
andckydb.set
. If you had separate locks, there would be chance for a data race. - For
ckydb.clear
, updateindex
first. - For
ckydb.delete
, updateindex
last. - For
ckydb.set
of a new key (i.e. not an update), updateindex
last. - For
ckydb.set
of pre-existing key, updatememtable
orcache
last as index would already be up-to-date. - For
store.vacuum
task andstore.delete
, there will be adel_file_lock
within store to avoid conflicts.
Acknowledgments
- We can do nothing without God (John 15: 5). Glory be to Him.
- Some of these ideas were adapted from leveldb. Thanks.
License
Copyright (c) 2022 Martin Ahindura. All implementations are licensed under the MIT License
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file ckydb-0.0.4.tar.gz
.
File metadata
- Download URL: ckydb-0.0.4.tar.gz
- Upload date:
- Size: 14.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.7.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | be0bd9326994bc4336a232a0e16c319d6b2f3b3336852a5c459e37035e60d5fc |
|
MD5 | 9dd32b2f753848be4cbf63d9900ca4e0 |
|
BLAKE2b-256 | c1fbc5e1c6680c986655813b78f4be329d108b93967bbfdfa0de8421f50e9da6 |
File details
Details for the file ckydb-0.0.4-py3-none-any.whl
.
File metadata
- Download URL: ckydb-0.0.4-py3-none-any.whl
- Upload date:
- Size: 12.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.7.13
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0d9f9641461d24f76fa026e30b2a5f6058da1323a1f97d62c114fe4dc35ef5a4 |
|
MD5 | 11162ef906b2d20d8d2c8b39cc0b9f65 |
|
BLAKE2b-256 | 4ee8e0b89ebca36cc08f00677f28a56dd1b34151bf03bbdf39e99651c7ed8290 |