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S CALABLE D ECENTRALIZED D E-DUPLICATION S TORE. Prakash Chandrasekaran – Anand Gupta Gautham Narayanasamy – Vijayaraghavan Subbaiah. Motivation. Importance of storage space Finding enough space to meet the demands of the customers has been a huge challenge for cloud providers.
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SCALABLE DECENTRALIZED DE-DUPLICATION STORE Prakash Chandrasekaran – Anand Gupta Gautham Narayanasamy – Vijayaraghavan Subbaiah
Motivation • Importance of storage space • Finding enough space to meet the demands of the customers has been a huge challenge for cloud providers. • Saving significant resources during web crawling, indexing, and search. • Backup Strategies • To backup the data and replicate them across many geographical locations. • Need for devising ingenious techniques to use the storage space more efficiently.
Deduplication • Removing duplicate copies of files and storing only the pointers to the original copy. • Block-level deduplication • Allows more granularity and hence offers a greater reduction in storage space. • Requires more processing power when compared to file-level deduplication. • Use case • Storage of snapshots of virtual machine (VM) images in a virtualized cloud environment. • Detecting exact duplicates and near duplicates in web pages.
Cassandra Schema • create keyspaceminhash; • create column family minhash_chunks with column_type=Super; • create column family minhash_filerecipewith column_type=Super; • create column family minhash_fullhash; • create keyspacefiles; • create column family files_minhash;
Data Distribution Client / Application Cassandra Cluster Load Balancing Cassandra Nodes
Data Flow in Cassandra OS Snapshot file / Web page Start Chunking Process Chunks Compute minhash and fullhash Full hash MinHash Cassandra Cluster Check full hash already exists File input to Client File Name Match Check file already exists Insert <fileid , minhash> Insert <minhash,filerecipe> Insert <minhash, chunkData> Insert <minhash, fullhash> Client
System Efficiency • Calculating the total amount of space saved. • Demonstrate the extent of similarity in various snapshots and web pages. • The overhead associated with file storage and retrieval in our system.