Data Integrity in hadoop distributed file system

HDFS transparently checksums all data written to it and by default verifies checksums when reading data. Datanodes are responsible for verifying the data they receive before storing the data and its checksum. This applies to data that they receive from clients and from other datanodes during replication. A client writing data sends it to a pipeline of datanodes, and the last datanode in the pipeline verifies the checksum. If the datanode detects an error, the client receives a subclass of IOException, which it should handle in an application-specific manner.

When clients read data from datanodes, they verify checksums as well, comparing them with the ones stored at the datanodes. Each datanode keeps a persistent log of checksum verifications, so it knows the last time each of its blocks was verified. When a client successfully verifies a block, it tells the datanode, which updates its log. Keeping statistics such as these is valuable in detecting bad disks.

In addition to block verification on client reads, each datanode runs a DataBlockScanner in a background thread that periodically verifies all the blocks stored on the datanode.

Because HDFS stores replicas of blocks, it can heal corrupted blocks by copying one of the good replicas to produce a new, uncorrupt replica. The way this works is that if a client detects an error when reading a block, it reports the bad block and the datanode it was trying to read from to the namenode before throwing a ChecksumException. The namenode marks the block replica as corrupt so it doesn’t direct any more clients to it or try to copy this replica to another datanode. It then schedules a copy of the block to be replicated on another datanode, so its replication factor is back at the expected level. Once this has happened, the corrupt replica is deleted.

Note : It is possible to disable verification of checksums by passing false to the setVerifyChecksum() method on FileSystem before using the open() method to read a file. The same effect is possible from the shell by using the -ignoreCrc option with the -get or the equivalent -copyToLocal command. This feature is useful if you have a corrupt file that you want to inspect so you can decide what to do with it. You can find a file’s checksum with hadoop fs -checksum. This is useful to check whether two files in HDFS have the same contents.

 

LocalFileSystem

The Hadoop LocalFileSystem performs client-side checksumming. This means that when you write a file called filename, the filesystem client transparently creates a hidden file, .filename.crc, in the same directory containing the checksums for each chunk of the file. The chunk size is controlled by the file.bytes-per-checksum property, which defaults to 512 bytes. The chunk size is stored as metadata in the .crc file, so the file can be read back correctly even if the setting for the chunk size has changed. Checksums are verified when the file is read, and if an error is detected, LocalFileSystem throws a ChecksumException.

Note : It is, however, possible to disable checksums, which is typically done when the underlying filesystem supports checksums natively. This is accomplished by using RawLocalFileSystem in place of LocalFileSystem.

Checksums are fairly cheap to compute (in Java, they are implemented in native code), typically adding a few percent overhead to the time to read or write a file. For most applications, this is an acceptable price to pay for data integrity.

Leave a Reply

Your email address will not be published. Required fields are marked *