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Date: Sun, 22 Nov 2015 09:13:10 +0000 (UTC)
From: "Nadav Har'El (JIRA)" <jira@apache.org>
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Subject: [jira] [Commented] (CASSANDRA-10728) Hash used in repair does not
 include partition key
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    [ https://issues.apache.org/jira/browse/CASSANDRA-10728?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15020906#comment-15020906 ] 

Nadav Har'El commented on CASSANDRA-10728:
------------------------------------------

Identical values, yes, but not identical keys...

> Hash used in repair does not include partition key
> --------------------------------------------------
>
>                 Key: CASSANDRA-10728
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-10728
>             Project: Cassandra
>          Issue Type: Bug
>            Reporter: Nadav Har'El
>            Priority: Minor
>
> When the repair code builds the Merkle Tree, it appears to be using AbstractCompactedRow.update() to calculate a partition's hash. This method's documentation states that it calculates a "digest with the data bytes of the row (not including row key or row size).". The code itself seems to agree with this comment.
> However, I believe that not including the row (actually, partition) key in the hash function is a mistake: This means that if two nodes have the same data but different key, repair would not notice this discrepancy. Moreover, if two different keys have their data switched - or have the same data - again this would not be noticed by repair. Actually running across this problem in a real repair is not very likely, but I can imagine seeing it easily in an hypothetical use case where all partitions have exactly the same data and just the partition key matters.
> I am sorry if I'm mistaken and the partition key is actually taken into account in the Merkle tree, but I tried to find evidence that it does and failed. Glancing over the code, it almost seems that it does use the key: Validator.add() calculates rowHash() which includes the digest (without the partition key) *and* the key's token. But then, the code calls MerkleTree.TreeRange.addHash() on that tuple, and that function conspicuously ignores the token, and only uses the digest.


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