I have a question about this statement: When rows get above a few 10¹s of MB things can slow down, when they get above 50 MB they can be a pain, when they get above 100MB it¹s a warning sign. And when they get above 1GB, well you you don¹t want to know what happens then.
I tested a data model that I created. Here¹s the schema for the table in question: CREATE TABLE bdn_index_pub ( tree INT, pord INT, hpath VARCHAR, PRIMARY KEY (tree, pord) ); As a test, I inserted 100 million records. tree had the same value for every record, and I had 100 million values for pord. hpath averaged about 50 characters in length. My understanding is that all 100 million strings would have been stored in a single row, since they all had the same value for the first component of the primary key. I didn¹t look at the size of the table, but it had to be several gigs (uncompressed). Contrary to what Aaron says, I do want to know what happens, because I didn¹t experience any issues with this table during my test. Inserting was fast. The last batch of records inserted in approximately the same amount of time as the first batch. Querying the table was fast. What I didn¹t do was test the table under load, nor did I try this in a multi-node cluster. If this is bad, can somebody suggest a better pattern? This table was designed to support a query like this: select hpath from bdn_index_pub where tree = :tree and pord >= :start and pord <= :end. In my application, most trees will have less than a million records. A handful will have 10¹s of millions, and one of them will have 100 million. If I need to break up my rows, my first instinct would be to divide each tree into blocks of say 10,000 and change tree to a string that contains the tree and the block number. Something like this: 17:0, 0, /¹ 17:0, 9999, ¹/a/b/c¹ 17:1,10000, /a/b/d¹ I¹d then need to issue an extra query for ranges that crossed block boundaries. Any suggestions on a better pattern? Thanks Robert From: Aaron Morton <aa...@thelastpickle.com> Reply-To: <user@cassandra.apache.org> Date: Tuesday, December 10, 2013 at 12:33 AM To: Cassandra User <user@cassandra.apache.org> Subject: Re: Exactly one wide row per node for a given CF? >> But this becomes troublesome if I add or remove nodes. What effectively I >> want is to partition on the unique id of the record modulus N (id % N; where >> N is the number of nodes). This is exactly the problem consistent hashing (used by cassandra) is designed to solve. If you hash the key and modulo the number of nodes, adding and removing nodes requires a lot of data to move. >> I want to be able to randomly distribute a large set of records but keep them >> clustered in one wide row per node. Sounds like you should revisit your data modelling, this is a pretty well known anti pattern. When rows get above a few 10¹s of MB things can slow down, when they get above 50 MB they can be a pain, when they get above 100MB it¹s a warning sign. And when they get above 1GB, well you you don¹t want to know what happens then. It¹s a bad idea and you should take another look at the data model. If you have to do it, you can try the ByteOrderedPartitioner which uses the row key as a token, given you total control of the row placement. Cheers ----------------- Aaron Morton New Zealand @aaronmorton Co-Founder & Principal Consultant Apache Cassandra Consulting http://www.thelastpickle.com On 4/12/2013, at 8:32 pm, Vivek Mishra <mishra.v...@gmail.com> wrote: > So Basically you want to create a cluster of multiple unique keys, but data > which belongs to one unique should be colocated. correct? > > -Vivek > > > On Tue, Dec 3, 2013 at 10:39 AM, onlinespending <onlinespend...@gmail.com> > wrote: >> Subject says it all. I want to be able to randomly distribute a large set of >> records but keep them clustered in one wide row per node. >> >> As an example, lets say I¹ve got a collection of about 1 million records each >> with a unique id. If I just go ahead and set the primary key (and therefore >> the partition key) as the unique id, I¹ll get very good random distribution >> across my server cluster. However, each record will be its own row. I¹d like >> to have each record belong to one large wide row (per server node) so I can >> have them sorted or clustered on some other column. >> >> If I say have 5 nodes in my cluster, I could randomly assign a value of 1 - 5 >> at the time of creation and have the partition key set to this value. But >> this becomes troublesome if I add or remove nodes. What effectively I want is >> to partition on the unique id of the record modulus N (id % N; where N is the >> number of nodes). >> >> I have to imagine there¹s a mechanism in Cassandra to simply randomize the >> partitioning without even using a key (and then clustering on some column). >> >> Thanks for any help. >
