1. Introduction
1.1 Purpose of the system
The blocks should be persisted on disk so that the node can work with them after rebooting. DAG is persisted as well, but only block metainfo is stored there and potentially large parts of the block (i.e. its body containing deployed terms) are not included into block metainfo. However, occasionally the deployed terms are required in the Casper protocol. For example, creating a new block involves choosing non-conflicting tips which require comparing their deployed terms on intersection. Hence, a place where full blocks are persisted is required so that Casper could make lookups in it.
The purpose of this document is to provide a specification of such a block on-disk storage which follows the existing BlockStore API and have a potential to store tens of millions of blocksIn the RChain architecture, blocks are effectively unlimited in size because this allows validators to produce blocks with large payloads and larger fee structures. In a proof-of-stake system, allowing large blocks creates an incentive for validators to acquire user traffic, and therefore transactions. This represents a significant contrast to proof-of-work systems, where miners have an incentive to mine blocks whether transactions exist to fill them, or not.
In order to handle large block sizes, RChain's node software must segregate block storage into several parts. This document describes how the complete block data is stored on disk, how it can be accessed from within the node, and the semantics of the data structure and storage employed. Storage of the directed acyclic graph (DAG) is not covered here. (See <TBD>)
The node writes complete block data to disk, in order to minimize network synchronization across node restarts. If a node is down for extended periods, it will be forced to perform synchronization with others nodes in order to update both its RBlocks data store, the BlockDAG, and the LatestMessages table for validators. The algorithm by which this update occurs and the network protocols enabling it are beyond the scope of this document. (See <TBD>)
1.1.1 Use Cases
The most significant and obvious use case for RBlocks is retrieval of the raw block content for Casper and for Rholang's Tuplespace. Casper needs to be able to determine whether two DAG tips conflict with each other, or not. In the case where they do not conflict, Casper needs to merge the tips. In the case where they do conflict, it must select between them. As Casper updates its notion of which transactions are preferred, it must provide this data to the Rholang interpreter's replay functionality to allow the Tuplespace to update its internal state according to the selected branch of the BlockDAG.
1.2 Design goals
The design goals of the block storage include:
- Looking up a block by its hash
- Inserting a new blockhash-block pair
- Storing the block bodies with little disk space overhead
- Storing tens of millions of blocks without significant performance hit
- Avoiding full database corruption on system crashes
1.3 Definitions, acronyms, and abbreviations
1.4 References
2. Current software architecture
The existing API for block storage is represented by BlockStore trait.
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The proposed implementation will reuse the existing trait for API, but asMap() method should be removed from it as it would be harmful to use such a method once the number of blocks will surpass several thousands.
3. Proposed software architecture
3.1 Overview
The proposed implementation LMDBIndexBlockStore of the existing API is a combination of an index backed up LMDB and a file containing an arbitrarily ordered sequence of block bodies.
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Other operations defined in BlockStore API can be implemented in the similar fashion.
3.2 Software/hardware mapping
3.2.1 Memory allocation
LMDB index is the only data structure which contributes to memory usage as LMDB uses memory-mapping. One key-value pair in LMDB index consists out of 32 bytes of block hash and 8 bytes of file offset. Hence, 40 bytes are needed to store one key-value pair and 1 GiB of RAM is able to hold almost 27M pairs. However, this does not include the overhead by LMDB for storing B+ tree layout which according to several benchmarks is quite high and can reach ~70%. After taking this in consideration, the approximate amount of pairs 1 GiB can handle is ~16M.
3.2.2 Disk Memory
The calculations for LMDB index memory allocation are also true for its disk space usage (including the overhead).
Block bodies are variable in size and it is impossible to calculate how much disk space they use up and the proposed solution's overhead is only 4 bytes (length of the body in bytes) per block body which add only 1 GiB of overhead every ~270M blocks.
3.3 Persistent data management
Storing blockhash-bodyoffset pairs is delegated to LMDB. A single pair's structure is shown on the following figure.
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Block bodies are stored in the specified file and written in arbitrary order. A header containing the size of the body preceded the actual content of the body as shown on the following figure.
3.4 Global software control
Gets, finds and puts require acquiring the lock and hence mutually exclusive.
3.5 Boundary conditions
- On node startup LMDB is initialized using the provided configuration and the block body file is opened
- On node shutdown shutdowns LMDB and closes the block body file
- On node error LMDB will not have to do any additional actions as it is system crash resistant. The block body storage can have some partially-written data in the end of the file, but index will not point to this corrupted part of the file as index is updated after the successful write to the block body file.
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