Hyperledger Fabric: An Overview of its Transaction Validation Feature


Hyperledger Fabric, a blockchain implementation hosted by the Linux Foundation, has been the subject of a series of articles in the last few issues of OSFY. In this issue, we take a look at how transactions are validated in the blockchain.

During the simulation of a transaction by an endorser, a read-write set is prepared for the transaction. The read set contains a list of unique keys and their committed versions that the transaction reads during simulation. The write set contains a list of unique keys and their new values that the transaction writes, though there can be overlap with the keys present in the read set. A delete marker is set, in the place of a new value for the key if the update performed by the transaction is to delete the key. If the transaction writes a value multiple times for a key, only the last written value is retained. Also, if a transaction reads a value for a key, the value in the committed state is returned even if the transaction has updated the value for the key before issuing the read. In other words, read-your-writes semantics are not supported. Or, the versions of the keys are recorded only in the read set; the write set just contains the list of unique keys and their latest values set by the transaction.

There could be various schemes for implementing versions. The minimal requirement for a versioning scheme is to produce non-repeating identifiers for a given key. For instance, using monotonically increasing numbers for versions can be one such scheme. In the current implementation, we use a blockchain height-based versioning scheme in which the height of the committing transaction is used as the latest version for all the keys modified by the transaction. In this scheme, the height of a transaction is represented by a tuple, txNumber, which is the height of the transaction within the block.

The following is an illustration of a sample read-write set prepared by simulating a hypothetical transaction. In the following example, the use of incremental numbers represents the versions.


<NsReadWriteSet name=”chaincode1”>


<read key=”K1”, version=”1”>

<read key=”K2”, version=”1”>



<write key=”K1”, value=”V1”

<write key=”K3”, value=”V2”

<write key=”K4”, isDelete=”true”




Additionally, if the transaction performs a range query during simulation, the range query as well as its results will be added to the read-write set as query information.

Transaction validation using a read-write set

A committer uses the read set portion of the read-write set for checking the validity of a transaction and the write set portion of the read-write set to update the versions and the values of the affected keys.

In the validation phase, a transaction is considered valid if the version of each key present in the read set of the transaction matches the version for the same key in the world state – assuming that all the preceding valid transactions, including the preceding transactions in the same block, are committed. An additional validation is performed if the read-write set also contains one or more query information.

This additional validation should ensure that no key has been inserted, deleted or updated in the super range, i.e., the union of the ranges of results captured in the query information. In other words, if we re-execute any of the range queries that the transaction performed during simulation while validating the committed state, it should yield the same results that were observed by the transaction at the time of simulation. This check ensures that if a transaction observes phantom items during commit, the transaction should be marked as invalid. This phantom protection is limited to range queries, i.e., the GetStateByRange function in the chaincode that is not yet implemented for other queries – the GetQueryResult function in the chaincode. Other queries are at risk of phantoms and should therefore only be used in read-only transactions that are not submitted to ordering, unless the application can guarantee the stability of the result set between simulation and validation/commit time.

If a transaction passes the validity check, the committer uses the write set for updating the world state. In the update phase, for each key present in the write set, the value in the world state for the same key is set to the value as specified in the write set. Further, the version of the key in the world state is changed to reflect the latest version.

The following example helps with understanding the semantics. For the purpose of this example, the presence of a key, k, in the world state is represented by a tuple (k, ver, val) where ver is the latest version of the key k having val as its value.

Now, consider a set of five transactions T1, T2, T3, T4 and T5, all simulated on the same snapshot of the world state. The following snippet shows the snapshot of the world state against which the transactions are simulated, and the sequence of read and write activities performed by each of these transactions. Also note that transactions with multiple read-write sets are not yet supported.

World state: (k1,1,v1), (k2,1,v2), (k3,1,v3), (k4,1,v4), (k5,1,v5)

T1 -> Write(k1, v1’), Write(k2, v2’)

T2 -> Read(k1), Write(k3, v3’)

T3 -> Write(k2, v2’’)

T4 -> Write(k2, v2’’’), read(k2)

T5 -> Write(k6, v6’), read(k5)

Now assume that these transactions are ordered in the sequence of T1,..,T5, which could be contained in a single block or different blocks:

  • T1 passes validation because it does not perform any read. Further, the tuples of keys k1 and k2 in the world state are updated to (k1,2,v1’), (k2,2,v2’).
  • T2 fails validation because it reads a key, k1, which was modified by a preceding transaction T1.
  • T3 passes the validation because it does not perform a read. Further, the tuple of the key, k2, in the world state is updated to (k2,3,v2’).
  • T4 fails the validation because it reads a key, k2, which was modified by a preceding transaction T1.
  • T5 passes validation because it reads a key, k5, which was not modified by any of the preceding transactions.


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