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librdb's Introduction

librdb - DRAFT

This is a C library for parsing RDB files.

The Parser is implemented in the spirit of SAX parser. It fires off a series of events as it reads the RDB file from beginning to end, and callbacks to handlers registered on selected types of data.

Current status

The project is currently in its early phase and is considered to be a draft. At present, the parser is only capable of handling string and list data types. We are actively seeking feedback on the design, API, and implementation to refine the project before proceeding with further development. Community contributions are welcome, yet please note that the codebase is still undergoing significant changes and may evolve in the future.

Getting Started

To build and run tests, you need to have cmocka unit testing framework installed and then:

make

If you just wish to get a basic understanding of the library's functionality, without running tests:

make lib 
make example

To see parser internal state printouts, execute the command export LIBRDB_DEBUG_DATA=1 beforehand.

Motivation behind this project

There is a genuine need by the Redis community for a versatile RDB file parser that can export data, perform data analysis, or merely extract raw data from RDB and RESTORE it against a live Redis server. However, available parsers have shortcomings in some aspects such as lack of long-term support, lagging far behind the latest Redis release, and usually not being optimized for memory, performance, or high-traffic streaming for production environments. Additionally, most of them are not written in C, which limits the reuse of Redis components and potential to contribute back to Redis repo. To address these issues, it is worthwhile to develop a new parser with a modern architecture, that maybe can also challenge the current integrated RDB parser of Redis and even replace it in the future.

Replacing the integrated RDB parser of Redis?

It is necessary to address first the reasons and missing features in the available parser, making replacing it a feasible option:

  1. The current parser is not designed to extend and customize it.
  2. Lacks of a unit testing framework.
  3. Does not support asynchronous parsing - That is, today reading of RDB sources is possible only in blocking IO mode, without the option to let Redis thread to carry on to other tasks and notify it asynchronously once a read operation is done.
  4. Doesn’t support pause and resume capabilities - A parsing of RDB is being made from start till completion as a single operation, without the option to indicate the parser to pause and save its state, in order to do other tasks in between.
  5. Once we decide to write RDB parser library, it is better to maintain a single parser rather than two.

Although it is challenging to develop a reusable and extensible parser that can match in performance, according to our initial evaluation as long as the new parser will avoid redundant copies and allocation of data, it is expected that it will show similar performance, or minor degradation at most, and yet we will gain all the advantages mentioned above. Having said that, our primary focus is to develop an “independent” RDB parser library.

Main building blocks

The RDB library parser composed of 3 main building blocks:

   +--------+     +--------+     +----------+
   | READER | --> | PARSER | --> | HANDLERS |
   +--------+     +--------+     +----------+

Reader

The Reader gives interface to the parser to access the RDB source. As first phase we will support:

  • Reading from a file (Status: Done)
  • Reading from a socket (Status: Todo)
  • User defined reader (Status: Done)

Possible extensions might be reading from S3, gz file, or a live redis instance.

This block is optional. As an alternative, the parser can be fed with chunks of data that hold RDB payload.

Parser

The Parser is the core engine. It will parse RDB file and trigger registered handlers.

The parser supports 3 sets of handlers to register, at 3 different levels of the parsed data:

Level0 - Registration on raw data

For example, if a user wants to restore from RDB source, then he doesn't care much about the different data-types, neither the internal RDB data structure, only to get raw data of whatever serialized and replay it against a live Redis server with RESTORE command. In that case registration on Level0 will do the magic.

Level1 - Registration on RDB data-structures

If required to analyze memory consumption, for example, then there is no escape but to inspect "low-level" data structures of RDB file. The best way to achieve it, is registration at level1 and pouring the logic to analyze each of the RDB data-structures into corresponding callbacks.

Level2 - Registration on Redis data-types

If we only care about DB logical data-types, for example in order to export data to another framework, then we better register our callbacks at level2.

Note, the set of handlers at Level1 get the data further parsed than the one "below it" at Level0. The same goes between Level2 and Level1 correspondingly.

Handlers

The Handlers represent a set of builtin or user-defined functions that will be called on the parsed data. Future plan to support built-in Handlers:

  • Convert RDB to JSON file handlers. (Status: WIP)
  • Convert RDB to RESP protocol handlers. (Status: Todo)
  • Memory Analyze (Status: Todo)

Using multiple sets of Handlers

It is possible to attach to parser more than one set of handlers at the same level. That is, for a given data at a given level, the parser will call each of the handlers that registered at that level.

One reason to do so can be because usually retrieving RDB file is the most time-consuming task of the parser, and it can save time by making a single parse yet invoke multiple sets of handlers.

More common reason is that a handlers can be used also as a Filter to decide whether to propagate data to the next set of handlers in-line (Such built-in filters can be found at extension library of this project). Note that for any given level, order of calls to handlers will be the opposite to order of their registration to that level. It's also possible to mix multiple registrations from level1 and level2, but not level0.

Usage

Following examples avoid error check to keep it concise. Full example can be found in examples directory.

  • Converting RDB file to JSON file:

    RdbParser *parser = RDB_createParserRdb(NULL);
    RDBX_createReaderFile(parser, "dump.rdb");
    RDBX_createHandlersRdb2Json(parser, encoding, "db.json", RDB_LEVEL_DATA);
    RDB_parse(parser); 
    RDB_deleteParser(parser); /* delete also reader & Handlers */
    
  • Parsing RDB file to RESP Commands:

    RdbParser *parser = RDB_createParserRdb(NULL);
    RDBX_createReaderFile(parser, "dump.rdb");
    RDBX_CreateHandlersRdbRaw2Redis(parser, encoding, sockfd_Redis);
    RDB_parse(parser);
    RDB_deleteParser(parser);
    
  • Parsing RDB file with user callbacks:

    RdbRes myHandleNewKey(RdbParser *p, void *userData,  RdbBulk key,...) { 
        printf("%s\n", key);
        return RDB_OK;
    } 
    
    RdbParser *parser = RDB_createParserRdb(NULL);
    RDBX_createReaderFile(parser, "dump.rdb");
    RdbHandlersRawCallbacks callbacks = { .handleNewKey = myHandleNewKey };
    RDB_createHandlersRaw(parser, &callbacks, myUserData, NULL);
    RDB_parse(parser);
    RDB_deleteParser(parser);
    
  • Use builtin Handlers (filters) to propagate only specific keys

    RdbParser *parser = RDB_createParserRdb(NULL);
    RDBX_createReaderFile(parser, "dump.rdb");
    RDBX_createHandlersRdb2Json(parser, encoding, "redis.json", RDB_LEVEL_DATA);
    RDBX_createHandlersFilterKey(parser, "id_*", 0, RDB_LEVEL_DATA);
    RDB_parse(parser);
    RDB_deleteParser(parser);
    
  • Parsing in memory data (without reader)

    unsigned char rdbContent[] =  {'R', 'E', 'D', 'I', 'S', .... };
    RdbParser *parser = RDB_createParserRdb(NULL);
    RDBX_createHandlersRdb2Json(parser, encoding, "redis.json", RDB_LEVEL_DATA);
    RDB_parseBuff(parser, rdbContent, sizeof(rdbContent), 1 /*EOF*/);
    RDB_deleteParser(parser);
    

Whether it is Reader or Handlers, once a new block is created, it is being attached to the parser and the parse will take ownership and will release the blocks either during its own destruction, or when newer block replacing old one.

Advanced

Customized Reader

The built-in readers should be sufficient for most purposes. However, if they do not meet your specific needs, you can use the RDB_createReaderRdb() helper function to create a custom reader with its own reader function. The built-in reader file (readerFile.c) can serve as a code reference for this purpose.

Asynchronous parser

The parser has been designed to handle asynchronous situation where it may temporarily not have data to read from the RDB-reader, or not feed yet with more input buffers.

Building on what was discussed previously, a reader can be implemented to support asynchronous reads by returning RDB_STATUS_WAIT_MORE_DATA for read requests. In such a case, it's necessary to provide a mechanism for indicating to the application when the asynchronous operation is complete, so the application can call RDB_parse() again. The async indication for read completion from the customized reader to the application is beyond the scope of this library. A conceptual invocation of such flow can be:

  myAsyncReader = RDB_createReaderRdb(p, myAsyncRdFunc, myAsyncRdData, myAsyncRdDeleteFunc);
  while(RDB_parse(p) == RDB_STATUS_WAIT_MORE_DATA) {
     my_reader_completed_await(myAsyncReader); 
  }

Another way to work asynchronously with the parser is just feeding the parser with chunks of streamed buffers by using the RDB_parseBuff() function:

  int parseRdb2Json(int file_descriptor, const char *fnameOut)
  {
    RdbStatus status;
    const int BUFF_SIZE = 200000;
    RdbParser *parser = RDB_createParserRdb(NULL);
    RDBX_createHandlersRdb2Json(parser, encoding, fnameOut, RDB_LEVEL_DATA);
    void *buf = malloc(BUFF_SIZE);
    do {                        
        int bytes_read = read(file_descriptor, buf, BUFF_SIZE);
        if (bytes_read < 0)  break; /* error */
        status = RDB_parseBuff(parser, buf, bytes_read, bytes_read == 0);
    } while (status == RDB_STATUS_WAIT_MORE_DATA);
    RDB_deleteParser(parser);
    free(buf);
  } 

Cancel parser execution

To cancel parsing in the middle of execution, the trigger should come from the registered handlers, Simply by returning RDB_ERR_CANCEL_PARSING. If the parser is using builtin handlers for parsing, and yet, you want that the parser will stop when some condition is met, then it is required to write a dedicated customized handlers, user-defined callbacks, to give this indication and register it as well.

Pause parser and resume

At times, the application may need to execute additional tasks during parsing intervals, such as updating a progress bar or performing other computations. To facilitate this, the parser can be configured with a pause interval that specifies the number of bytes to be read from RDB source before pausing. This means that each time the parser is invoked, it will continue parsing until it has read a number of bytes equal to or greater than the configured interval, at which point it will automatically pause and return 'RDB_STATUS_PAUSED' in order to allow the application to perform other tasks. Example:

  size_t intervalBytes = 1048576;  
  RdbParser *parser = RDB_createParserRdb(memAlloc);
  RDBX_createReaderFile(parser, "dump.rdb");
  RDBX_createHandlersRdb2Json(parser, encoding, "db.json", RDB_LEVEL_DATA);
  RDB_setPauseInterval(parser, intervalBytes);
  while (RDB_parse(parser) == RDB_STATUS_PAUSED) {
      /* do something else in between */
  } 
  RDB_deleteParser(parser);

Note, if pause interval has elapsed and at the same time the parser need to return indication to wait for more data, then the parser will suppress pause indication and return RDB_STATUS_WAIT_MORE_DATA instead.

However, there may be cases where it is more appropriate for the callback handlers to determine when to suspend the parser. In such cases, the callback should call RDB_pauseParser() to pause the parser. Note that, the parser may still call one or a few more callbacks before actual pausing.

Special cautious should be given when using this feature along with RDB_parseBuff(). Since the parser doesn't owns the buffer it reads from, when the application intends to call again to RDB_parseBuff() to resume parsing after pause, it must call with the same buffer that it supplied before the pause and only partially processed. The function RDB_parseBuff() will verify that the buffer reference is identical as before and continue with the same offset it reached. This also implies that the buffer must remain persistent in such a scenario. Whereas it might seem redundant API to pass again the same values on resume, yet it highlights the required persistence of the reused buffer.

Memory optimization

The optimization of memory usage is a major focus for the parser, which is also evident in its API. The application can optionally choose not only to customize the malloc function used internally by the parser, but also the method for allocating data passed to the callbacks. This includes the options:

  1. Using parser internal stack
  2. Using parser internal heap allocation (with refcount support for zero-copy).
  3. Using external allocation
  4. Using external allocation unless data is already prefetched in memory.

The external allocation options give the opportunity to allocate the data by the parser in specific layout, as the application expects. For more information, lookup for structure RdbBulkAllocType at librdb-api.h.

Implementation notes

The Redis RDB file format consists of a series of opcodes followed by the actual data that is being persisted. Each opcode represents a specific operation that needs to be performed when encoding or decoding data. The parsing process has been organized into separate parsing-elements which primarily align with RDB opcodes. Each parsing-element that correspond to RDB opcode usually carries out the following steps:

  1. Reads from RDB file required amount of data to process current state of parsing-element.
  2. If required, calls app's callbacks or store the parsed data for later use.
  3. Updates the state of the next parsing-element to be called.

Async support

As mentioned above, instead of blocking the parser on read command, the reader (and in turn the parser) can return to the caller RDB_STATUS_WAIT_MORE_DATA and will be ready to be called again to continue parsing once more data become available.

In such scenario, any incomplete parsing-element will preserve its current state. As for any data that has already been read from the RDB reader - it cannot be read again from the reader. To address this issue, a unique bulk-pool data structure is used to route all data being read from the RDB reader. It stores a reference to the allocations in a queue, and enable to rollback and replay later once more data becomes available, in an attempt to complete the parsing-element state. The rollback command basically rewinds the queue of allocation and allows the exact same sequence of allocation requests to be provided to the caller, however, instead of creating new allocations, the allocator returns the next item in the queue. Otherwise, if the parser managed to reach a new parsing-element state, then all cached data in the pool will be flushed.

The bulk-pool is also known as parsing-element's cache. To learn more about it, refer to the comment at the start of the file bulkAlloc.h.

Parsing-Element states

Having gained understanding of the importance of bulk-pool rollback and replay for async parsing, it is necessary to address two crucial questions:

  1. If we are parsing, say a large list, is it necessary for the parser to rollback all the way to the beginning of current parsing-element?
  2. If the parser has already called app callbacks, will it call them again on rollback?

1. Parsing-element internal states

It is essential to break down complex parsing elements with multiple items into internal iterative states. This ensures that any asynchronous event will cause the parser to rollback to its last valid iterative state, rather than all the way back to the beginning of the parsing element. For instance, in the case of a list opcode, the corresponding parsing element (See function elementList) will comprise an entry state that parses the number of elements in the list from the RDB file and an iterative state that parses each subsequent node in the list. In case of rollback only the last node will be parsed again rather than parsing the entire list from start.

The parsing-element cache gets flushed on each parsing-element state transition. This prevents the parser from reading outdated buffers from the cache that belong to the previous state in case of a rollback scenario, ensuring that consecutive states are clearly differentiated.

2. Defining Safe-state

Regarding the second question, before making a callback to the application, the parsing element must first ensure that its state reached a safe state. That is, there should be no new attempts to read the RDB file until the end of current state that may result in rollbacks. Otherwise, on rollback, the parser may end up calling the same application callback more than once.

Caching and garbage-collector

As mentioned above the parsing-element cache will be flushed whenever next parsing-element is set or when the parsing-element state is updated. This way we also gain along the way a cache with garbage collector capabilities at hand that can also serve parsing-element for its own internal allocations, for example, after reading compressed data from RDB file, the parser can allocate a new buffer from cache for decompression operation without the worry to release it at the end or in case of an error.

State machine parser

The parsing-elements in the implementation are partially designed using a state machine approach. Each parsing-element calls indirectly the next one, and the main parsing loop triggers the next parsing element through the parserMainLoop function. This approach not only adds an extra layer of control to the parser along execution steps, but also enables parsing of customized RDB files or even specific parts of the file. This functionality can be further enhanced as needed.

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