Dealing with Int64 value with Booksleeve - redis

I have a question about Marc Gravell's Booksleeve library.
I tried to understand how booksleeve deal the Int64 value (i have billion long value in Redis actually)
I used reflection to undestand the Set long value overrides.
// BookSleeve.RedisMessage
protected static void WriteUnified(Stream stream, long value)
{
if (value >= 0L && value <= 99L)
{
int i = (int)value;
if (i <= 9)
{
stream.Write(RedisMessage.oneByteIntegerPrefix, 0, RedisMessage.oneByteIntegerPrefix.Length);
stream.WriteByte((byte)(48 + i));
}
else
{
stream.Write(RedisMessage.twoByteIntegerPrefix, 0, RedisMessage.twoByteIntegerPrefix.Length);
stream.WriteByte((byte)(48 + i / 10));
stream.WriteByte((byte)(48 + i % 10));
}
}
else
{
byte[] bytes = Encoding.ASCII.GetBytes(value.ToString());
stream.WriteByte(36);
RedisMessage.WriteRaw(stream, (long)bytes.Length);
stream.Write(bytes, 0, bytes.Length);
}
stream.Write(RedisMessage.Crlf, 0, 2);
}
I don't understand why, with more than two digits int64, the long is encoding in ascii?
Why don't use byte[] ? I know than i can use byte[] overrides to do this, but i just want to understand this implementation to optimize mine. There may be a relationship with the Redis storage.
By advance thank you Marc :)
P.S : i'm still very enthusiastic about your next major version, than i can use long value key instead of string.

It writes it in ASCII because that is what the redis protocol demands.
If you look carefully, it is always encoded as ASCII - but for the most common cases (0-9, 10-99) I've special-cased it, as these are very simple results:
x => $1\r\nX\r\n
xy => $2\r\nXY\r\n
where x and y are the first two digits of a number in the range 0-99, and X and Y are those digits (as numbers) offset by 48 ('0') - so decimal 17 becomes the byte sequence (in hex):
24-32-0D-0A-31-37-0D-0A
Of course, that can also be achieved simply via the writing each digit sequentially and offsetting the digit value by 48 ('0'), and handling the negative sign - I guess the answer there is simply "because I coded it the simple but obviously correct way". Consider the value -123 - which is encoded as $4\r\n-123\r\n (hey, don't look at me - I didn't design the protocol). It is slightly awkward because it needs to calculate the buffer length first, then write that buffer length, then write the value - remembering to write in the order 100s, 10s, 1s (which is much harder than writing the other way around).
Perfectly willing to revisit it - simply: it works.
Of course, it becomes trivial if you have a scratch buffer available - you just write it in the simple order, then reverse the portion of the scratch buffer. I'll check to see if one is available (and if not, it wouldn't be unreasonable to add one).
I should also clarify: there is also the integer type, which would encode -123 as :-123\r\n - however, from memory there are a lot of places this simply does not work.

Related

Chessprogramming: how to get a single move out of a bitboard attack-mask most efficently

How can I get efficiently a single move out of an attack mask, that looks like this:
....1...
1...1...
.1..1..1
..1.1.1.
...111..
11111111
..1.11..
.1..1.1.
for a queen.
What I've done in the past, is to get the square-indices of every single possible move from the queen by counting the trailing zeros (bitScanForward)
and after I generated the new move i removed this square from the attack mask and continued with the next attack-square. Is there any technic to get the single attack bits directly?
I think what you are describing is already the most efficient way. Looping over the bitboard until it is zero and pick one move at a time.
To sketch the idea with some code, it could look like this:
using Bitboard = uint64_t; // 64 bit unsigned integer
pMoves createAllMoves(Bitboard mask, int from_sq, Move* pMoves) {
while(moves != 0) {
int to_sq = findAndClearSetBit(mask);
*pMoves++ = createMove(from_sq, to_sq);
}
return pMoves;
}
The findAndClearSetBit function can choose any set bit, but commonly on today's hardware, finding the least significant bit is most efficient. If you are using GCC or Clang, you can use __builtin_ctzll which should be optimized to the specific hardware:
int findAndClearSetBit(Bitboard& mask) {
int sq = __builtin_ctzll(mask); // find least significant bit
mask &= mask - 1; // clear least significant bit
return sq;
}
If I am not mistaken, your existing function bitScanForward is already an implementation to find the least significant bit. So, you can use it to get a portable version.

How to read 8-byte integers in GMS 2.x?

I need to read 8-byte integers from a stream. I could not find any documentation how to read 8-byte integers in DM. It would be something similar to a long long integer.
Is there a trick how to stream 8-byte integers from file in GMS 2.x ?
We can use the "Stream" object to read/import data of various kinds. Please refer to the DM Help > Scripting > File Input and Output:
Other examples can also be found at DM-Script-Database :
Read-Ser (http://donation.tugraz.at/dm/source_codes/127)
JEMS_.ems file reader (http://donation.tugraz.at/dm/source_codes/108)
Hope this helps.
I used the following (stupid) method to do so:
number readint32(object s){
number stream_byte_order=2
number result=0
TagGroup tg = NewTagGroup();
tg.TagGroupSetTagAsLong( "SInt32_0", 0 )
TagGroupReadTagDataFromStream( tg, "SInt32_0", s, stream_byte_order );
tg.TagGroupGetTagAsLong( "SInt32_0", result)
return result
}
number readint64(object s){
//new for reading 8-byte integer in TIA ver >3.7
//DM automatic convert result to float when the second 4-byte >1
number result = readint32(s)+ (readint32(s)*4294967296)
// 4294967296 equals to 0xFFFFFFFF in hex form
return result
}
It works with reading ser <2GB, but does not for larger file. I still did not figure it out...
#09-04-2016
Now i got a solution to the data offset problem in ser:
Here is the solution:
Void b_readint64(object s, number &lo, number &hi){
//new for reading 8-byte (64bit) integer in TIA ver >3.7
//read the low and high section individually and later work
//together with StreamSetPos32singed, StreamSetPos64 funcsions
lo = b_readint32(s)
hi = b_readint32(s)
}
Void StreamSetPos32Signed(object s, number base, number lo){
if (lo>0) StreamSetPos(s, base, lo)
else StreamSetPos(s, base, 4294967296+lo)
}
Void StreamSetPos64(object s, number base, number lo, number hi){
if (hi!=0){
StreamSetPos(s, base, 0)
for (number i=0; i<hi; i++) StreamSetPos(s, 1, 4294967296)
StreamSetPos32Signed(s, 1, lo)
} else StreamSetPos32signed(s, base, lo)
}
BTW, I just uploaded this upgraded script to
http://portal.tugraz.at/portal/page/portal/felmi/DM-Script/DM-Script-Database
There is nothing like an 8-byte integer in DigitalMicrograph. You can use the streaming to read in two successive 4-byte sections as integers (See answer above) and then display them as binary using binary() or hexadecimal using hex(), but you will have to do the maths yourself for the "meaning" of the 8-byte integer (storing it as real-number). You can use the binary operators & | ^ for bitwise numeric, when needed.

Storing integers in a redis ordered set?

I have a system which deals with keys that have been turned into unsigned long integers (by packing short sequences into byte strings). I want to try storing these in Redis, and I want to do it in the best way possible. My concern is mainly memory efficiency.
From playing with the online REPL I notice that the two following are identical
zadd myset 1.0 "123"
zadd myset 1.0 123
This means that even if I know I want to store an integer, it has to be set as a string. I notice from the documentation that keys are just stored as char*s and that commands like SETBIT indicate that Redis is not averse to treating strings as bytestrings in the client. This hints at a slightly more efficient way of storing unsigned longs than as their string representation.
What is the best way to store unsigned longs in sorted sets?
Thanks to Andre for his answer. Here are my findings.
Storing ints directly
Redis keys must be strings. If you want to pass an integer, it has to be some kind of string. For small, well-defined sets of values, Redis will parse the string into an integer, if it is one. My guess is that it will use this int to tailor its hash function (or even statically dimension a hash table based on the value). This works for small values (examples being the default values of 64 entries of a value of up to 512). I will test for larger values during my investigation.
http://redis.io/topics/memory-optimization
Storing as strings
The alternative is squashing the integer so it looks like a string.
It looks like it is possible to use any byte string as a key.
For my application's case it actually didn't make that much difference storing the strings or the integers. I imagine that the structure in Redis undergoes some kind of alignment anyway, so there may be some pre-wasted bytes anyway. The value is hashed in any case.
Using Python for my testing, so I was able to create the values using the struct.pack. long longs weigh in at 8 bytes, which is quite large. Given the distribution of integer values, I discovered that it could actually be advantageous to store the strings, especially when coded in hex.
As redis strings are "Pascal-style":
struct sdshdr {
long len;
long free;
char buf[];
};
and given that we can store anything in there, I did a bit of extra Python to code the type into the shortest possible type:
def do_pack(prefix, number):
"""
Pack the number into the best possible string. With a prefix char.
"""
# char
if number < (1 << 8*1):
return pack("!cB", prefix, number)
# ushort
elif number < (1 << 8*2):
return pack("!cH", prefix, number)
# uint
elif number < (1 << 8*4):
return pack("!cI", prefix, number)
# ulonglong
elif number < (1 << 8*8):
return pack("!cQ", prefix, number)
This appears to make an insignificant saving (or none at all). Probably due to struct padding in Redis. This also drives Python CPU through the roof, making it somewhat unattractive.
The data I was working with was 200000 zsets of consecutive integer => (weight, random integer) × 100, plus some inverted index (based on random data). dbsize yields 1,200,001 keys.
Final memory use of server: 1.28 GB RAM, 1.32 Virtual. Various tweaks made a difference of no more than 10 megabytes either way.
So my conclusion:
Don't bother encoding into fixed-size data types. Just store the integer as a string, in hex if you want. It won't make all that much difference.
References:
http://docs.python.org/library/struct.html
http://redis.io/topics/internals-sds
I'm not sure of this answer, it's more of a suggestion than anything else. I'd have to give it a try and see if it works.
As far as I can tell, Redis only supports UTF-8 strings.
I would suggest grabbing a bit representation of your long integer and pad it accordingly to fill up the nearest byte. Encode each set of 8 bytes to a UTF-8 string (ending up with 8x*utf8_char* string) and store that in Redis. The fact that they're unsigned means that you don't care about that first bit but if you did, you could add a flag to the string.
Upon retrieving the data, you have to remember to pad each character to 8 bytes again as UTF-8 will use less bytes for the representation if the character can be stored with less bytes.
End result is that you store a maximum of 8 x 8 byte characters instead of (possibly) a maximum of 64 x 8 byte characters.

What are the practical uses of modulus (%) in programming? [duplicate]

This question already has answers here:
Closed 12 years ago.
Possible Duplicate:
Recognizing when to use the mod operator
What are the practical uses of modulus? I know what modulo division is. The first scenario which comes to my mind is to use it to find odd and even numbers, and clock arithmetic. But where else I could use it?
The most common use I've found is for "wrapping round" your array indices.
For example, if you just want to cycle through an array repeatedly, you could use:
int a[10];
for (int i = 0; true; i = (i + 1) % 10)
{
// ... use a[i] ...
}
The modulo ensures that i stays in the [0, 10) range.
I usually use them in tight loops, when I have to do something every X loops as opposed to on every iteration..
Example:
int i;
for (i = 1; i <= 1000000; i++)
{
do_something(i);
if (i % 1000 == 0)
printf("%d processed\n", i);
}
One use for the modulus operation is when making a hash table. It's used to convert the value out of the hash function into an index into the array. (If the hash table size is a power of two, the modulus could be done with a bit-mask, but it's still a modulus operation.)
To print a number as string, you need the modulus to find the value of a digit.
string number_to_string(uint number) {
string result = "";
while (number != 0) {
result = cast(char)((number % 10) + '0') ~ result;
// ^^^^^^^^^^^
number /= 10;
}
return result;
}
For the control number of international bank account numbers, the mod97 technique.
Also in large batches to do something after n iterations. Here is an example for NHibernate:
ISession session = sessionFactory.openSession();
ITransaction tx = session.BeginTransaction();
for ( int i=0; i<100000; i++ ) {
Customer customer = new Customer(.....);
session.Save(customer);
if ( i % 20 == 0 ) { //20, same as the ADO batch size
//Flush a batch of inserts and release memory:
session.Flush();
session.Clear();
}
}
tx.Commit();
session.Close();
The usual implementation of buffered communications uses circular buffers, and you manage them with modulus arithmetic.
For languages that don't have bitwise operators, modulus can be used to get the lowest n bits of a number. For example, to get the lowest 8 bits of x:
x % 256
which is equivalent to:
x & 255
Cryptography. That alone would account for an obscene percentage of modulus (I exaggerate, but you get the point).
Try the Wikipedia page too:
Modular arithmetic is referenced in number theory, group theory, ring theory, knot theory, abstract algebra, cryptography, computer science, chemistry and the visual and musical arts.
In my experience, any sufficiently advanced algorithm is probably going to touch on one more of the above topics.
Well, there are many perspectives you can look at it. If you are looking at it as a mathematical operation then it's just a modulo division. Even we don't need this as whatever % do, we can achieve using subtraction as well, but every programming language implement it in very optimized way.
And modulu division is not limited to finding odd and even numbers or clock arithmetic. There are hundreds of algorithms which need this module operation, for example, cryptography algorithms, etc. So it's a general mathematical operation like other +, -, *, /, etc.
Except the mathematical perspective, different languages use this symbol for defining built-in data structures, like in Perl %hash is used to show that the programmer declared a hash. So it all varies based on the programing language design.
So still there are a lot of other perspectives which one can do add to the list of use of %.

Is there a practical limit to the size of bit masks?

There's a common way to store multiple values in one variable, by using a bitmask. For example, if a user has read, write and execute privileges on an item, that can be converted to a single number by saying read = 4 (2^2), write = 2 (2^1), execute = 1 (2^0) and then add them together to get 7.
I use this technique in several web applications, where I'd usually store the variable into a field and give it a type of MEDIUMINT or whatever, depending on the number of different values.
What I'm interested in, is whether or not there is a practical limit to the number of values you can store like this? For example, if the number was over 64, you couldn't use (64 bit) integers any more. If this was the case, what would you use? How would it affect your program logic (ie: could you still use bitwise comparisons)?
I know that once you start getting really large sets of values, a different method would be the optimal solution, but I'm interested in the boundaries of this method.
Off the top of my head, I'd write a set_bit and get_bit function that could take an array of bytes and a bit offset in the array, and use some bit-twiddling to set/get the appropriate bit in the array. Something like this (in C, but hopefully you get the idea):
// sets the n-th bit in |bytes|. num_bytes is the number of bytes in the array
// result is 0 on success, non-zero on failure (offset out-of-bounds)
int set_bit(char* bytes, unsigned long num_bytes, unsigned long offset)
{
// make sure offset is valid
if(offset < 0 || offset > (num_bytes<<3)-1) { return -1; }
//set the right bit
bytes[offset >> 3] |= (1 << (offset & 0x7));
return 0; //success
}
//gets the n-th bit in |bytes|. num_bytes is the number of bytes in the array
// returns (-1) on error, 0 if bit is "off", positive number if "on"
int get_bit(char* bytes, unsigned long num_bytes, unsigned long offset)
{
// make sure offset is valid
if(offset < 0 || offset > (num_bytes<<3)-1) { return -1; }
//get the right bit
return (bytes[offset >> 3] & (1 << (offset & 0x7));
}
I've used bit masks in filesystem code where the bit mask is many times bigger than a machine word. think of it like an "array of booleans";
(journalling masks in flash memory if you want to know)
many compilers know how to do this for you. Adda bit of OO code to have types that operate senibly and then your code starts looking like it's intent, not some bit-banging.
My 2 cents.
With a 64-bit integer, you can store values up to 2^64-1, 64 is only 2^6. So yes, there is a limit, but if you need more than 64-its worth of flags, I'd be very interested to know what they were all doing :)
How many states so you need to potentially think about? If you have 64 potential states, the number of combinations they can exist in is the full size of a 64-bit integer.
If you need to worry about 128 flags, then a pair of bit vectors would suffice (2^64 * 2).
Addition: in Programming Pearls, there is an extended discussion of using a bit array of length 10^7, implemented in integers (for holding used 800 numbers) - it's very fast, and very appropriate for the task described in that chapter.
Some languages ( I believe perl does, not sure ) permit bitwise arithmetic on strings. Giving you a much greater effective range. ( (strlen * 8bit chars ) combinations )
However, I wouldn't use a single value for superimposition of more than one /type/ of data. The basic r/w/x triplet of 3-bit ints would probably be the upper "practical" limit, not for space efficiency reasons, but for practical development reasons.
( Php uses this system to control its error-messages, and I have already found that its a bit over-the-top when you have to define values where php's constants are not resident and you have to generate the integer by hand, and to be honest, if chmod didn't support the 'ugo+rwx' style syntax I'd never want to use it because i can never remember the magic numbers )
The instant you have to crack open a constants table to debug code you know you've gone too far.
Old thread, but it's worth mentioning that there are cases requiring bloated bit masks, e.g., molecular fingerprints, which are often generated as 1024-bit arrays which we have packed in 32 bigint fields (SQL Server not supporting UInt32). Bit wise operations work fine - until your table starts to grow and you realize the sluggishness of separate function calls. The binary data type would work, were it not for T-SQL's ban on bitwise operators having two binary operands.
For example .NET uses array of integers as an internal storage for their BitArray class.
Practically there's no other way around.
That being said, in SQL you will need more than one column (or use the BLOBS) to store all the states.
You tagged this question SQL, so I think you need to consult with the documentation for your database to find the size of an integer. Then subtract one bit for the sign, just to be safe.
Edit: Your comment says you're using MySQL. The documentation for MySQL 5.0 Numeric Types states that the maximum size of a NUMERIC is 64 or 65 digits. That's 212 bits for 64 digits.
Remember that your language of choice has to be able to work with those digits, so you may be limited to a 64-bit integer anyway.