If i have an entity with a primary key id and an unique column name. Is there any difference whether i do a SQL request findById(long id) or findByName(String name). Can a search for the primary key be done in O(1) while the other one works in O(n)? Which data structures are used for saving them?
The difference is speed :
Running SQL query against Integer will always be faster than running against a string.
From the perspective of order complexity of the operation, then the two are equivalent.
As others have pointed out, an integer lookup is generally faster than a string lookup. Here are three reasons:
The index would typically be smaller because, integers are 4 bytes and strings are typically bigger.
Indexes on fixed length keys have some additional efficiencies in the tree structure (no need to "find the end of the string").
In many databases, strings incur additional overhead to handle collations.
That said, another factor is that the primary key is often clustered in many databases. This eliminates the final lookup of the row in data pages -- which might be a noticeable efficiency as well. Note that not all databases support clustered indexes, so this is not true in all cases.
If both columns were INTEGER, then the answer would be "no". A PRIMARY KEY is effectively a UNIQUE constraint on a column and little more. Additionally, as usually they both cause internal indexes to be created, again they behave basically the same way.
In your specific case, however, the NAME column is a string. Even though it has a UNIQUE constraint, by virtue of its data type you will incur in some performance loss.
As your question is probably dictated by "ease of use" to some extent (for your debugging purposes it's certainly easy to remember the "name" than it is to remember the "id") the questions you need to ask yourself are:
Will the NAME column always be unique or could it be change to something not unique? Should it actually be unique in the first place (maybe they set it up wrong)?
How many rows do you expect in your table? This is important to know as while a small table won't really show any performance issue, a high cardinality may start to show some.
How many transactions/second do you expect? If it's an internal application or a small amateurial project, you can live with the NAME column being queried whereas if you need extreme scalability you should stay away from it.
I'm looking for 3rdparty service in order to create/emulate something similar to a Postgres sequence database object.
I need this thread safe functionality in order to be able to ask it for next, unique Long value. I'm going to use this value as a surrogate key for my Spring Boot/Neoj4 application entities.
The main criterion is a speed. It should be pretty fast and durable(not only in memory but also persisted to HDD in order to survive after crashes and restarts)
Also, I don't want to go with UUID because I have to expose these IDs within my web application url parameters and in case of UUID my urls look awful. I want to go with a plain Long values for IDs.
Could you please suggest some database/service/technology that can be installed on my server and called for the unique IDs ?
UPDATED
Is it possible to implement fault-tolerant(persisted) AtomicLong sequence with Apache ZooKeeper or Hazelcast ? If so, is there any open source implementation of this solution that can be downloaded and used?
Something like Snowflake (https://github.com/twitter/snowflake/releases/tag/snowflake-2010) or snowcast (https://github.com/noctarius/snowcast) might be of interest to you.
If you want just numbers, why did you don't want to concatenate 2 longs from UUID (most + least)
According to your comment's question:
Yes, concatenated (not summed!) value from this methods with numbers filled leading 0 to full long length will gurantee all the same as UUID by itself (because it is kind of UUIDs view).
We are working on a layered Java application that talks directly to Gemfire.
We need to be able to generate unique "long" sequence numbers, guaranteed unique across all nodes of the application. (Not all nodes are clustered)
Normally I would create a sequence in Oracle, but in this case, even though our Gemfire configuration has a connection to the relational database for write behind persistence, our application has no other knowledge of the database.
What would be the best way to generate those guaranteed unique long values, without going to the database?
The first question to ask yourself is do you really need a long sequence number (monotonically increasing long integer) or do you just need a globally unique identifier (like a UUID).
The most performant solution is going to be a globally unique id and I would just suggest using a GUID.
If you need a globally unique monotonically increasing long value (long sequence) then you will have to use some distributed locking and increment a value in the region. The method for this and performance depends on the type of region you are using.
Look at Region.replace(K, V, V). It can perform globally atomic updates to values under specific region definitions. You may need to consider a region that just has your sequences if your current region type is not sufficiently defined.
I've generally implemented sequence number generation using database sequences in the past.
e.g. Using Postgres SERIAL type http://www.neilconway.org/docs/sequences/
I'm curious though as how to generate sequence numbers for large distributed systems where there is no database. Does anybody have any experience or suggestions of a best practice for achieving sequence number generation in a thread safe manner for multiple clients?
OK, this is a very old question, which I'm first seeing now.
You'll need to differentiate between sequence numbers and unique IDs that are (optionally) loosely sortable by a specific criteria (typically generation time). True sequence numbers imply knowledge of what all other workers have done, and as such require shared state. There is no easy way of doing this in a distributed, high-scale manner. You could look into things like network broadcasts, windowed ranges for each worker, and distributed hash tables for unique worker IDs, but it's a lot of work.
Unique IDs are another matter, there are several good ways of generating unique IDs in a decentralized manner:
a) You could use Twitter's Snowflake ID network service. Snowflake is a:
Networked service, i.e. you make a network call to get a unique ID;
which produces 64 bit unique IDs that are ordered by generation time;
and the service is highly scalable and (potentially) highly available; each instance can generate many thousand IDs per second, and you can run multiple instances on your LAN/WAN;
written in Scala, runs on the JVM.
b) You could generate the unique IDs on the clients themselves, using an approach derived from how UUIDs and Snowflake's IDs are made. There are multiple options, but something along the lines of:
The most significant 40 or so bits: A timestamp; the generation time of the ID. (We're using the most significant bits for the timestamp to make IDs sort-able by generation time.)
The next 14 or so bits: A per-generator counter, which each generator increments by one for each new ID generated. This ensures that IDs generated at the same moment (same timestamps) do not overlap.
The last 10 or so bits: A unique value for each generator. Using this, we don't need to do any synchronization between generators (which is extremely hard), as all generators produce non-overlapping IDs because of this value.
c) You could generate the IDs on the clients, using just a timestamp and random value. This avoids the need to know all generators, and assign each generator a unique value. On the flip side, such IDs are not guaranteed to be globally unique, they're only very highly likely to be unique. (To collide, one or more generators would have to create the same random value at the exact same time.) Something along the lines of:
The most significant 32 bits: Timestamp, the generation time of the ID.
The least significant 32 bits: 32-bits of randomness, generated anew for each ID.
d) The easy way out, use UUIDs / GUIDs.
You could have each node have a unique ID (which you may have anyway) and then prepend that to the sequence number.
For example, node 1 generates sequence 001-00001 001-00002 001-00003 etc. and node 5 generates 005-00001 005-00002
Unique :-)
Alternately if you want some sort of a centralized system, you could consider having your sequence server give out in blocks. This reduces the overhead significantly. For example, instead of requesting a new ID from the central server for each ID that must be assigned, you request IDs in blocks of 10,000 from the central server and then only have to do another network request when you run out.
Now there are more options.
Though this question is "old", I got here, so I think it might be useful to leave the options I know of (so far):
You could try Hazelcast. In it's 1.9 release it includes a Distributed implementation of java.util.concurrent.AtomicLong
You can also use Zookeeper. It provides methods for creating sequence nodes (appended to znode names, though I prefer using version numbers of the nodes). Be careful with this one though: if you don't want missed numbers in your sequence, it may not be what you want.
Cheers
It can be done with Redisson. It implements distributed and scalable version of AtomicLong. Here is example:
Config config = new Config();
config.addAddress("some.server.com:8291");
Redisson redisson = Redisson.create(config);
RAtomicLong atomicLong = redisson.getAtomicLong("anyAtomicLong");
atomicLong.incrementAndGet();
If it really has to be globally sequential, and not simply unique, then I would consider creating a single, simple service for dispensing these numbers.
Distributed systems rely on lots of little services interacting, and for this simple kind of task, do you really need or would you really benefit from some other complex, distributed solution?
There are a few strategies; but none that i know can be really distributed and give a real sequence.
have a central number generator. it doesn't have to be a big database. memcached has a fast atomic counter, in the vast majority of cases it's fast enough for your entire cluster.
separate an integer range for each node (like Steven Schlanskter's answer)
use random numbers or UUIDs
use some piece of data, together with the node's ID, and hash it all (or hmac it)
personally, i'd lean to UUIDs, or memcached if i want to have a mostly-contiguous space.
Why not use a (thread safe) UUID generator?
I should probably expand on this.
UUIDs are guaranteed to be globally unique (if you avoid the ones based on random numbers, where the uniqueness is just highly probable).
Your "distributed" requirement is met, regardless of how many UUID generators you use, by the global uniqueness of each UUID.
Your "thread safe" requirement can be met by choosing "thread safe" UUID generators.
Your "sequence number" requirement is assumed to be met by the guaranteed global uniqueness of each UUID.
Note that many database sequence number implementations (e.g. Oracle) do not guarantee either monotonically increasing, or (even) increasing sequence numbers (on a per "connection" basis). This is because a consecutive batch of sequence numbers gets allocated in "cached" blocks on a per connection basis. This guarantees global uniqueness and maintains adequate speed. But the sequence numbers actually allocated (over time) can be jumbled when there are being allocated by multiple connections!
Distributed ID generation can be archived with Redis and Lua. The implementation available in Github. It produces a distributed and k-sortable unique ids.
I know this is an old question but we were also facing the same need and was unable to find the solution that fulfills our need.
Our requirement was to get a unique sequence (0,1,2,3...n) of ids and hence snowflake did not help.
We created our own system to generate the ids using Redis. Redis is single threaded hence its list/queue mechanism would always give us 1 pop at a time.
What we do is, We create a buffer of ids, Initially, the queue will have 0 to 20 ids that are ready to be dispatched when requested. Multiple clients can request an id and redis will pop 1 id at a time, After every pop from left, we insert BUFFER + currentId to the right, Which keeps the buffer list going. Implementation here
I have written a simple service which can generate semi-unique non-sequential 64 bit long numbers. It can be deployed on multiple machines for redundancy and scalability. It use ZeroMQ for messaging. For more information on how it works look at github page: zUID
Using a database you can reach 1.000+ increments per second with a single core. It is pretty easy. You can use its own database as backend to generate that number (as it should be its own aggregate, in DDD terms).
I had what seems a similar problem. I had several partitions and I wanted to get an offset counter for each one. I implemented something like this:
CREATE DATABASE example;
USE example;
CREATE TABLE offsets (partition INTEGER, offset LONG, PRIMARY KEY (partition));
INSERT offsets VALUES (1,0);
Then executed the following statement:
SELECT #offset := offset from offsets WHERE partition=1 FOR UPDATE;
UPDATE offsets set offset=#offset+1 WHERE partition=1;
If your application allows you, you can allocate a block at once (that was my case).
SELECT #offset := offset from offsets WHERE partition=1 FOR UPDATE;
UPDATE offsets set offset=#offset+100 WHERE partition=1;
If you need further throughput an cannot allocate offsets in advance you can implement your own service using Flink for real time processing. I was able to get around 100K increments per partition.
Hope it helps!
The problem is similar to:
In iscsi world, where each luns/volumes have to be uniquely identifiable by the initiators running on the client side.
The iscsi standard says that the first few bits have to represent the Storage provider/manufacturer information, and the rest monotonically increasing.
Similarly, one can use the initial bits in the distributed system of nodes to represent the nodeID and the rest can be monotonically increasing.
One solution that is decent is to use a long time based generation.
It can be done with the backing of a distributed database.
My two cents for gcloud. Using storage file.
Implemented as cloud function, can easily be converted to a library.
https://github.com/zaky/sequential-counter
I'm planning on using client provided UUID's as the primary key in several tables in a MySQL Database.
I've come across various mechanisms for storing UUID's in a MySQL database but nothing that compares them against each other. These include storage as:
BINARY(16)
CHAR(16)
CHAR(36)
VARCHAR(36)
2 x BIGINT
Are there any better options, how do the options compare against each other in terms of:
storage size?
query overhead? (index issues, joins etc.)
ease of inserting and updating values from client code? (typically Java via JPA)
Are there any differences based on which version of MySQL your running, or the storage engine? We're currently running 5.1 and were planning on using InnoDB. I'd welcome any comments based on practical experience of trying to use UUIDs. Thanks.
I would go with storing it in a Binary(16) column, if you are indeed set on using UUIDs at all. something like 2x bigint would be quite cumbersome to manage. Also, i've heard of people reversing them because the start of the UUIDs on the same machine tend to be the same at the beginning, and the different parts are at the end, so if you reverse them, your indexes will be more efficient.
Of course, my instinct says that you should be using auto increment integers unless you have a really good reason for using the UUID. One good reason is generating unique keys accross different databases. The other option is that you plan to have more records than an INT can store. Although not many applications really need things like this. THere is not only a lot of efficiency lost when not using integers for your keys, and it's also harder to work with them. they are too long to type in, and passing them around in your URLs make the URLs really long. So, go with the UUID if you need it, but try to stay away.
I have used UUIDs for smart client online/offline storage and data synchronization and for databases that I knew would have to be merged at some point. I have always used char(36) or char(32)(no dashes). You get a slight performance gain over varchar and almost all databases support char. I have never tried binary or bigint. One thing to be aware of, is that char will pad with spaces if you do not use 36 or 32 characters. Point being, don't write a unit test that sets the ID of an object to "test" and then try to find it in the database. ;)