Messagepack in redis - c++

I am creating a large map in messagepack using c++. I need multiple languages to be able to have access to the data.
How would I store this as a string in redis? Is there an idiomatic way to put this in memory or should I use the following?
msgpack::packer<msgpack::sbuffer> pk2(&buffer2);
pk2.pack_map(2);
pk2.pack(std::string("x"));
pk2.pack(3);
pk2.pack(std::string("y"));
pk2.pack(3.4321);
Redox rdx;
rdx.connect()
rdx.command<int>({"rpush", "key_name", buffer2.data()})

Sensible depends on what you're trying to achieve. You didn't explain why you're using the Redis List data structure to store your msgpack data, so unless there's some unspecified reason to do so, I'd go with simple Strings.
Also, the example provided does not make sense IMO because you're not providing the key name to rpush into.
Edit: thanks for correcting the snippet
Lastly, if you're using msgpack for your data, you can do really interesting things with Lua scripting as Redis provides the cmsgpack library to manipulate packed messages.

Related

Retrieving object back without serialization and copy

I am working on a software stack where it is composed of three different entities:
abc_data - holding the data as "plain" data structure
abc_instance - acting as an API
abc_repo - for internal conversions from abc_data to abc_instance. It includes methods using logic for an easy access and queries of the data (e.g., get_a() or get_b())
When creating a new abc_instance from abc_data, the abc_repo converts the abc_data to a different internal representation for fast access (e.g., vectors, maps) without holding the original abc_data representation anymore. However, this way it is not possible to go back to abc_data from a abc_instance.
What would be the best and elegant way to retrieve the abc_data back from a formerly created abc_instance, ideally without any further conversion.
NOTE: Please understand that I don't want to use de/serialization here. Also keeping a copy of the abc_data is not an option.
Any pointers and help would be appreciated. Thanks in advance!

Should use a stream or container when working with network, binary data and serialization

I am working on a TCP server using boost asio and I got lost with choosing the best data type to work with when dealing with byte buffers.
Currently I am using std::vector<char> for everything. One of the reasons is that most of examples of asio use vectors or arrays. I receive data from network and put it in a buffer vector. Once a packet is available, it is extracted from the buffer and decrypted/decompressed if needed (both operations may result in more amount of data). Then multiple messages are extracted from the payload.
I am not happy with this solution because it involves inserting and removing data from vectors constantly, but it does the job.
Now I need to work on data serialization. There is not an easy way to read or write arbitrary data types from a char vector so I ended up implementing a "buffer" that hides a vector inside, and allows to write (wrapper for insert) and read (wrapper for casting) from it. Then I can write uint16 code; buffer >> code; and also add serialization/deserialization methods to other objects while keeping things simple.
The thing is that every time I think about this I feel like I am using the wrong data type as container for the binary data. Reasons are:
Streams already do a good job as potentially endless source of data input or data output. While in background this may result in inserting and removing data, probably does a better job than using a char vector.
Streams already allow to read or write basic data types, so I don't have to reinvent the wheel.
There is no need to access to a specific position of data. Usually I need to read or write sequentially.
In this case, are streams the best choice or is there something that I am not seeing?. And if so, is stringstream the one I should use?
Any reasons to avoid streams and work only with containers?
PD: I can not use boost serialization or any other existing solution because I don't have control over the network protocol.
Your approach seems fine. You might consider a deque instead of a vector if you're doing a lot of stealing from the end and erasing from the front, but if you use circular-buffer logic while iterating then this doesn't matter either.
You could switch to a stream, but then you're completely at the mercy of the standard library, its annoyances/oddities, and the semantics of its formatted extraction routines — if these are insufficient then you have to extract N bytes and do your own reinterpretation anyway, so you're back to square one but with added copying and indirection.
You say you don't need random-access, so that's another reason not to care either way. Personally I like to have random-access in case I need to resync, or seek-ahead, or seek-behind, or even just during debugging want to have better capabilities without having to suddenly refactor all my buffer code.
I don't think there's any more specific answer to this in the general case.

Data storage library for C++

I would like to use some tiny C++ library in my code, which would allow to do something like:
DataStore ds;
ds.open("data.bin");
int num=5;
std::string str="some text";
ds.put("key1",num);
ds.put("key2",str);
ds.get("key1");// returns int(5)
ds.get("key2");// returns std::string("some text")
The usage style doesn't have to be the same as that code example, but the principle should remain (get/set value of any type and store it in the file blob). The library should also not be SQL based, nor be an SQL wrapper. What are such libraries and what are their advantages?
EDIT: max 10k keys would be used, with approx. 100bytes data per key, file doesn't need to be portable between computers or OS, file shouldn't be editable with text editor (it looks more professional if it isn't) and doesn't have to be multi-threaded aware.
One option for you is to use BerkeleyDB and its C API, C++ API or C++ STL API:
BekeleyDB has a small footprint, is fast, mature and robust. Another advantage of BerkeleyDB is that most scripting languages like Python, Perl, etc. have bindings to it so you can manipulate (examine, visualize) the data with them.
The disadvantage is that all you can store in it is a key-value pair where both key and value are strings (or rather blobs), so you have to convert from C++ data types to strings/blobs.
It wouldn't be hard to create a class that does what you describe in a basic way. All you need is a some functions that can read/write keys, a tag for "what type is this" [perhaps combined with the size of the data stored, if we assume the data stored isn't enormous - and I mean a few MB per item or so]. You may find having some sort of "index structure" or "where is the next element" location references help.
There is a small problem with the way your ds.get(std::string) is shown: you can't actually return an int and a std::string from the same function. You may be able to write a function that takes a std::string as a reference, and another that takes an int as a reference, or some such.
It gets more interesting if you need to have many keys - at this point, you probably need some sort of hash or binary tree type organisation to search through the keys. 10k keys is probably not a big deal - if you store them in sorted order it gets easier.
file shouldn't be editable with text editor (it looks more professional if it isn't)
I must say, I don't agree with that. I find text editable files are VERY professional looking. The fact that it's binary is just making things awkward, and harder to deal with should something in the application not work as you wish (e.g. it stored the installation path, you moved it, and it no longer works, and since you can't start it, it won't allow you to edit that configuration).

Store and retrieve a Data structure

I have a situation where I'm parsing an xml file in c++(using libxml) and with the extracted info I'm creating a data structure on the fly & modifying the D.S according to the further extracted info from the parsed file. Now I need to save the D.S as it is, in secondary memory and I want to retrieve back the D.S from memory later so that I can continue working further without the need of creating the D.S once again. Can someone please help me out on how to do this?
I suggest using a library like Boost.Serialization for this.
I assume that 'secondary memory' is a hard drive or something. In that case use fwrite and fread, or in C++ overload << and >> if you want. How you do this depends on your data structure, if it has members that are pointers then things get a bit more complicated.
There's not enough info in your question to really help you.

How to handle changing data structures on program version update?

I do embedded software, but this isn't really an embedded question, I guess. I don't (can't for technical reasons) use a database like MySQL, just C or C++ structs.
Is there a generic philosophy of how to handle changes in the layout of these structs from version to version of the program?
Let's take an address book. From program version x to x+1, what if:
a field is deleted (seems simple enough) or added (ok if all can use some new default)?
a string gets longer or shorter? An int goes from 8 to 16 bits of signed / unsigned?
maybe I combine surname/forename, or split name into two fields?
These are just some simple examples; I am not looking for answers to those, but rather for a generic solution.
Obviously I need some hard coded logic to take care of each change.
What if someone doesn't upgrade from version x to x+1, but waits for x+2? Should I try to combine the changes, or just apply x -> x+ 1 followed by x+1 -> x+2?
What if version x+1 is buggy and we need to roll-back to a previous version of the s/w, but have already "upgraded" the data structures?
I am leaning towards TLV (http://en.wikipedia.org/wiki/Type-length-value) but can see a lot of potential headaches.
This is nothing new, so I just wondered how others do it....
I do have some code where a longer string is puzzled together from two shorter segments if necessary. Yuck. Here's my experience after 12 years of keeping some data compatible:
Define your goals - there are two:
new versions should be able to read what old versions write
old versions should be able to read what new versions write (harder)
Add version support to release 0 - At least write a version header. Together with keeping (potentially a lot of) old reader code around that can solve the first case primitively. If you don't want to implement case 2, start rejecting new data right now!
If you need only case 1, and and the expected changes over time are rather minor, you are set. Anyway, these two things done before the first release can save you many headaches later.
Convert during serialization - at run time, only keep the data in the "new format" in memory. Do necessary conversions and tests at persistence limits (convert to newest when reading, implement backward compatibility when writing). This isolates version problems in one place, helping to avoid hard-to-track-down bugs.
Keep a set of test data from all versions around.
Store a subset of available types - limit the actually serialized data to a few data types, such as int, string, double. In most cases, the extra storage size is made up by reduced code size supporting changes in these types. (That's not always a tradeoff you can make on an embedded system, though).
e.g. don't store integers shorter than the native width. (you might need to do that when you need to store long integer arrays).
add a breaker - store some key that allows you to intentionally make old code display an error message that this new data is incompatible. You can use a string that is part of the error message - then your old version could display an error message it doesn't know about - "you can import this data using the ConvertX tool from our web site" is not great in a localized application but still better than "Ungültiges Format".
Don't serialize structs directly - that's the logical / physical separation. We work with a mix of two, both having their pros and cons. None of these can be implemented without some runtime overhead, which can pretty much limit your choices in an embedded environment. At any rate, don't use fixed array/string lengths during persistence, that should already solve half of your troubles.
(A) a proper serialization mechanism - we use a bianry serializer that allows to start a "chunk" when storing, which has its own length header. When reading, extra data is skipped and missing data is default-initialized (which simplifies implementing "read old data" a lot in the serializationj code.) Chunks can be nested. That's all you need on the physical side, but needs some sugar-coating for common tasks.
(B) use a different in-memory representation - the in-memory reprentation could basically be a map<id, record> where id woukld likely be an integer, and record could be
empty (not stored)
a primitive type (string, integer, double - the less you use the easier it gets)
an array of primitive types
and array of records
I initially wrote that so the guys don't ask me for every format compatibility question, and while the implementation has many shortcomings (I wish I'd recognize the problem with the clarity of today...) it could solve
Querying a non existing value will by default return a default/zero initialized value. when you keep that in mind when accessing the data and when adding new data this helps a lot: Imagine version 1 would calculate "foo length" automatically, whereas in version 2 the user can overrride that setting. A value of zero - in the "calculation type" or "length" should mean "calculate automatically", and you are set.
The following are "change" scenarios you can expect:
a flag (yes/no) is extended to an enum ("yes/no/auto")
a setting splits up into two settings (e.g. "add border" could be split into "add border on even days" / "add border on odd days".)
a setting is added, overriding (or worse, extending) an existing setting.
For implementing case 2, you also need to consider:
no value may ever be remvoed or replaced by another one. (But in the new format, it could say "not supported", and a new item is added)
an enum may contain unknown values, other changes of valid range
phew. that was a lot. But it's not as complicated as it seems.
There's a huge concept that the relational database people use.
It's called breaking the architecture into "Logical" and "Physical" layers.
Your structs are both a logical and a physical layer mashed together into a hard-to-change thing.
You want your program to depend on a logical layer. You want your logical layer to -- in turn -- map to physical storage. That allows you to make changes without breaking things.
You don't need to reinvent SQL to accomplish this.
If your data lives entirely in memory, then think about this. Divorce the physical file representation from the in-memory representation. Write the data in some "generic", flexible, easy-to-parse format (like JSON or YAML). This allows you to read in a generic format and build your highly version-specific in-memory structures.
If your data is synchronized onto a filesystem, you have more work to do. Again, look at the RDBMS design idea.
Don't code a simple brainless struct. Create a "record" which maps field names to field values. It's a linked list of name-value pairs. This is easily extensible to add new fields or change the data type of the value.
Some simple guidelines if you're talking about a structure use as in a C API:
have a structure size field at the start of the struct - this way code using the struct can always ensure they're dealing only with valid data (for example, many of the structures the Windows API uses start with a cbCount field so these APIs can handle calls made by code compiled against old SDKs or even newer SDKs that had added fields
Never remove a field. If you don't need to use it anymore, that's one thing, but to keep things sane for dealing with code that uses an older version of the structure, don't remove the field.
it may be wise to include a version number field, but often the count field can be used for that purpose.
Here's an example - I have a bootloader that looks for a structure at a fixed offset in a program image for information about that image that may have been flashed into the device.
The loader has been revised, and it supports additional items in the struct for some enhancements. However, an older program image might be flashed, and that older image uses the old struct format. Since the rules above were followed from the start, the newer loader is fully able to deal with that. That's the easy part.
And if the struct is revised further and a new image uses the new struct format on a device with an older loader, that loader will be able to deal with it, too - it just won't do anything with the enhancements. But since no fields have been (or will be) removed, the older loader will be able to do whatever it was designed to do and do it with the newer image that has a configuration structure with newer information.
If you're talking about an actual database that has metadata about the fields, etc., then these guidelines don't really apply.
What you're looking for is forward-compatible data structures. There are several ways to do this. Here is the low-level approach.
struct address_book
{
unsigned int length; // total length of this struct in bytes
char items[0];
}
where 'items' is a variable length array of a structure that describes its own size and type
struct item
{
unsigned int size; // how long data[] is
unsigned int id; // first name, phone number, picture, ...
unsigned int type; // string, integer, jpeg, ...
char data[0];
}
In your code, you iterate through these items (address_book->length will tell you when you've hit the end) with some intelligent casting. If you hit an item whose ID you don't know or whose type you don't know how to handle, you just skip it by jumping over that data (from item->size) and continue on to the next one. That way, if someone invents a new data field in the next version or deletes one, your code is able to handle it. Your code should be able to handle conversions that make sense (if employee ID went from integer to string, it should probably handle it as a string), but you'll find that those cases are pretty rare and can often be handled with common code.
I have handled this in the past, in systems with very limited resources, by doing the translation on the PC as a part of the s/w upgrade process. Can you extract the old values, translate to the new values and then update the in-place db?
For a simplified embedded db I usually don't reference any structs directly, but do put a very light weight API around any parameters. This does allow for you to change the physical structure below the API without impacting the higher level application.
Lately I'm using bencoded data. It's the format that bittorrent uses. Simple, you can easily inspect it visually, so it's easier to debug than binary data and is tightly packed. I borrowed some code from the high quality C++ libtorrent. For your problem it's so simple as checking that the field exist when you read them back. And, for a gzip compressed file it's so simple as doing:
ogzstream os(meta_path_new.c_str(), ios_base::out | ios_base::trunc);
Bencode map(Bencode::TYPE_MAP);
map.insert_key("url", url.get());
map.insert_key("http", http_code);
os << map;
os.close();
To read it back:
igzstream is(metaf, ios_base::in | ios_base::binary);
is.exceptions(ios::eofbit | ios::failbit | ios::badbit);
try {
torrent::Bencode b;
is >> b;
if( b.has_key("url") )
d->url = b["url"].as_string();
} catch(...) {
}
I have used Sun's XDR format in the past, but I prefer this now. Also it's much easier to read with other languages such as perl, python, etc.
Embed a version number in the struct or, do as Win32 does and use a size parameter.
if the passed struct is not the latest version then fix up the struct.
About 10 years ago I wrote a similar system to the above for a computer game save game system. I actually stored the class data in a seperate class description file and if i spotted a version number mismatch then I coul run through the class description file, locate the class and then upgrade the binary class based on the description. This, obviously required default values to be filled in on new class member entries. It worked really well and it could be used to auto generate .h and .cpp files as well.
I agree with S.Lott in that the best solution is to separate the physical and logical layers of what you are trying to do. You are essentially combining your interface and your implementation into one object/struct, and in doing so you are missing out on some of the power of abstraction.
However if you must use a single struct for this, there are a few things you can do to help make things easier.
1) Some sort of version number field is practically required. If your structure is changing, you will need an easy way to look at it and know how to interpret it. Along these same lines, it is sometimes useful to have the total length of the struct stored in a structure field somewhere.
2) If you want to retain backwards compatibility, you will want to remember that code will internally reference structure fields as offsets from the structure's base address (from the "front" of the structure). If you want to avoid breaking old code, make sure to add all new fields to the back of the structure and leave all existing fields intact (even if you don't use them). That way, old code will be able to access the structure (but will be oblivious to the extra data at the end) and new code will have access to all of the data.
3) Since your structure may be changing sizes, don't rely on sizeof(struct myStruct) to always return accurate results. If you follow #2 above, then you can see that you must assume that a structure may grow larger in the future. Calls to sizeof() are calculated once (at compile time). Using a "structure length" field allows you to make sure that when you (for example) memcpy the struct you are copying the entire structure, including any extra fields at the end that you aren't aware of.
4) Never delete or shrink fields; if you don't need them, leave them blank. Don't change the size of an existing field; if you need more space, create a new field as a "long version" of the old field. This can lead to data duplication problems, so make sure to give your structure a lot of thought and try to plan fields so that they will be large enough to accommodate growth.
5) Don't store strings in the struct unless you know that it is safe to limit them to some fixed length. Instead, store only a pointer or array index and create a string storage object to hold the variable-length string data. This also helps protect against a string buffer overflow overwriting the rest of your structure's data.
Several embedded projects I have worked on have used this method to modify structures without breaking backwards/forwards compatibility. It works, but it is far from the most efficient method. Before long, you end up wasting space with obsolete/abandoned structure fields, duplicate data, data that is stored piecemeal (first word here, second word over there), etc etc. If you are forced to work within an existing framework then this might work for you. However, abstracting away your physical data representation using an interface will be much more powerful/flexible and less frustrating (if you have the design freedom to use such a technique).
You may want to take a look at how Boost Serialization library deals with that issue.