BF.SCANDUMP
BF.SCANDUMP key iterator
- Available in:
- Redis Stack / Bloom 1.0.0
- Time complexity:
- O(n), where n is the capacity
Begins an incremental save of the Bloom filter.
This command is useful for large Bloom filters that cannot fit into the DUMP
and RESTORE
model.
The first time this command is called, the value of iter
should be 0.
This command returns successive (iter, data)
pairs until (0, NULL)
to indicate completion.
Required arguments
key
is key name for a Bloom filter to save.
iterator
Iterator value; either 0 or the iterator from a previous invocation of this command
Return value
Returns one of these replies:
-
Array reply of Integer reply (Iterator) and [] (Data).
The Iterator is passed as input to the next invocation of
BF.SCANDUMP
. If Iterator is 0, then it means iteration has completed.The iterator-data pair should also be passed to
BF.LOADCHUNK
when restoring the filter. -
[] on error (invalid arguments, key not found, wrong key type, etc.)
Examples
redis> BF.RESERVE bf 0.1 10
OK
redis> BF.ADD bf item1
1) (integer) 1
redis> BF.SCANDUMP bf 0
1) (integer) 1
2) "\x01\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x05\x00\x00\x00\x02\x00\x00\x00\b\x00\x00\x00\x00\x00\x00\x00@\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x9a\x99\x99\x99\x99\x99\xa9?J\xf7\xd4\x9e\xde\xf0\x18@\x05\x00\x00\x00\n\x00\x00\x00\x00\x00\x00\x00\x00"
redis> BF.SCANDUMP bf 1
1) (integer) 9
2) "\x01\b\x00\x80\x00\x04 \x00"
redis> BF.SCANDUMP bf 9
1) (integer) 0
2) ""
redis> DEL bf
(integer) 1
redis> BF.LOADCHUNK bf 1 "\x01\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x05\x00\x00\x00\x02\x00\x00\x00\b\x00\x00\x00\x00\x00\x00\x00@\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x9a\x99\x99\x99\x99\x99\xa9?J\xf7\xd4\x9e\xde\xf0\x18@\x05\x00\x00\x00\n\x00\x00\x00\x00\x00\x00\x00\x00"
OK
redis> BF.LOADCHUNK bf 9 "\x01\b\x00\x80\x00\x04 \x00"
OK
redis> BF.EXISTS bf item1
(integer) 1
Python code:
chunks = []
iter = 0
while True:
iter, data = BF.SCANDUMP(key, iter)
if iter == 0:
break
else:
chunks.append([iter, data])
# Load it back
for chunk in chunks:
iter, data = chunk
BF.LOADCHUNK(key, iter, data)