Py-IBLT

A Python implementation of Invertible Bloom Lookup Tables

Invertible Bloom Lookup Table

From the abstract of the paper (2011):

We present a version of the Bloom filter data structure that supports not only the insertion, deletion, and lookup of key-value pairs, but also allows a complete listing of its contents with high probability, as long the number of key-value pairs is below a designed threshold. Our structure allows the number of key-value pairs to greatly exceed this threshold during normal operation. Exceeding the threshold simply temporarily prevents content listing and reduces the probability of a successful lookup. If later entries are deleted to return the structure below the threshold, everything again functions appropriately. We also show that simple variations of our structure are robust to certain standard errors, such as the deletion of a key without a corresponding insertion or the insertion of two distinct values for a key. The properties of our structure make it suitable for several applications, including database and networking applications that we highlight.

Notes

• Records that are deleted without a corresponding insert operation can be recovered with the get and list_entries functions.
• Error detection using hashValueSum as described in the paper is currently not implemented.
• Duplicate keys are not supported.

Usage

Constructor

Use the constructor to create a new IBLT:

from iblt import IBLT
t = IBLT( m, k, key_size, value_size, hash_key_sum_size=10, hash=None )

m is the amount of cells in underlying lookup table, and is closely related to the threshold value that determines how many key/value pairs the IBLT can hold before giving inconclusive answers to queries. k is the amount of hash functions to be used. key_size is maximum size for keys. value_size is maximum size for values. hash_key_sum_size is amount of bytes used for the hashkeySum field. hash is function( i, value ), where i is index of hash function and value is value to be hashed (or None for default hash functions).

Insert and delete

The insert function inserts a key/value pair into the IBLT.

t.insert( key, value )

The delete function likewise deletes a key/value pair from the IBLT.

t.delete( key, value )

The insert and delete functions do not have any return values.

Retrieving a value based on a key

The get function tries to retrieve a value by key and gives you additional information on how the operation went:

t.get( key )

For the get function, the return value is ( <Result>, <Value> ). The <Result> value can be one of the following four possibilities:

• IBLT.RESULT_GET_NO_MATCH It is certain that no such key exists in the table. <Value> is None.
• IBLT.RESULT_GET_MATCH The key was previously inserted into the table and the value is returned in <Value>.
• IBLT.RESULT_GET_DELETED_MATCH The key was found, but it had been deleted instead of inserted and the value is returned in <Value>.
• IBLT.RESULT_GET_INCONCLUSIVE It wasn't possible to determine if the key was in the table or not. <Value> is None.

Listing entries

The list_entries function tries to extract a complete list of all entries in the table. It either returns all entries or an incomplete list:

t.list_entries()

The return value of list_entries is ( <Result>, [<Entries>], [<Deleted entries>] ).

The <Result> value is one of two possibilities:

• IBLT.RESULT_LIST_ENTRIES_COMPLETE The entries lists are complete.
• IBLT.RESULT_LIST_ENTRIES_INCOMPLETE: It wasn't possible to extract a complete listing. Only the returned entries were recoverable.

The <Entries> list contains all recoverable entries that have been inserted into the table. Likewise, the <Deleted entries> list contains all recoverable entries that have been deleted from the table without being inserted.

Serializing and unserializing

Table instances have a serialize function, that takes no argument and serializes the data and metadata of the table for into a bitstring storage or communication.

Likewise, the IBLT class has a static unserialize function that takes the serialized bitstring and constructs a copy of the table from the bitstring.

# t is an IBLT instance
s = t.serialize()

# Prints True
print IBLT.unserialize( s ) == t

Serialized data format:

	[ Magic bytes ][  Header  ][ Data ]
    	4 bytes      24 bytes    

Magic bytes: 
	0x49 0x42 0x4C 0x54 (ASCII for IBLT)

Header:
    [ Cell count (m) ]
         32-bit uint

    [ Key sum length ][ Value sum length ]
        32-bit uint	      32-bit uint

    [ HashKeySum length ][ ValueKeySum length ]
        32-bit uint           32-bit uint

    [ # hash funcs (k) ]
        32-bit uint

Data:
    For each of the m cells:
        [ 	Count 	 ][ keySum ][ valueSum ][ hashKeySum ][ valueKeySum ]
          32-bit int

License

The MIT License (MIT)

Copyright (c) 2014 Jesper Borgstrup

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.