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https://issues.apache.org/jira/browse/CASSANDRA-4815?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13477218#comment-13477218
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Edward Capriolo commented on CASSANDRA-4815:
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As I mentioned towards the end of the ticket, this feature request is not to
support future theoretical use cases, it is to support the dominant current use
case. It is not just my use case. It is the use case that the Cassandra project
originally advocated.
http://www.slideshare.net/lomakin.andrey/apache-cassandra-part-1-principles-data-model
slide 30
-columns aren't fixed
-columns can be sorted
-columns can be queried for a certain range
I am fine if Cassandra adds new features that benefit from more schema, I am
fine with Cassandra adding collections and think these are a great idea. But I
see no technical reason why CQL can't support both old and new use cases. This
is especially disturbing since the project offers no eloquent way to get from
now to the future. Switching to COMPACT STORAGE is a pain and rewriting all the
data into a new collection based design is not necessarily a good use of
resources.
Someone once told me Avro was the future of Cassandra. I am asking for features
to support the now.
> Make CQL work naturally with wide rows
> --------------------------------------
>
> Key: CASSANDRA-4815
> URL: https://issues.apache.org/jira/browse/CASSANDRA-4815
> Project: Cassandra
> Issue Type: Wish
> Reporter: Edward Capriolo
>
> I find that CQL3 is quite obtuse and does not provide me a language useful
> for accessing my data. First, lets point out how we should design Cassandra
> data.
> 1) Denormalize
> 2) Eliminate seeks
> 3) Design for read
> 4) optimize for blind writes
> So here is a schema that abides by these tried and tested rules large
> production uses are employing today.
> Say we have a table of movie objects:
> Movie
> Name
> Description
> -< tags (string)
> -< credits composite(role string, name string )
> -1 likesToday
> -1 blacklisted
> The above structure is a movie notice it hold a mix of static and dynamic
> columns, but the other all number of columns is not very large. (even if it
> was larger this is OK as well) Notice this table is not just
> a single one to many relationship, it has 1 to 1 data and it has two sets of
> 1 to many data.
> The schema today is declared something like this:
> create column family movies
> with default_comparator=UTF8Type and
> column_metadata =
> [
> {column_name: blacklisted, validation_class: int},
> {column_name: likestoday, validation_class: long},
> {column_name: description, validation_class: UTF8Type}
> ];
> We should be able to insert data like this:
> set ['Cassandra Database, not looking for a seQL']['blacklisted']=1;
> set ['Cassandra Database, not looking for a seQL']['likesToday']=34;
> set ['Cassandra Database, not looking for a
> seQL']['credits-dir']='director:asf';
> set ['Cassandra Database, not looking for a
> seQL']['credits-jir]='jiraguy:bob';
> set ['Cassandra Database, not looking for a seQL']['tags-action']='';
> set ['Cassandra Database, not looking for a seQL']['tags-adventure']='';
> set ['Cassandra Database, not looking for a seQL']['tags-romance']='';
> set ['Cassandra Database, not looking for a seQL']['tags-programming']='';
> This is the correct way to do it. 1 seek to find all the information related
> to a movie. As long as this row does
> not get "large" there is no reason to optimize by breaking data into other
> column families. (Notice you can not transpose this
> because movies is two 1-to-many relationships of potentially different types)
> Lets look at the CQL3 way to do this design:
> First, contrary to the original design of cassandra CQL does not like wide
> rows. It also does not have a good way to dealing with dynamic rows together
> with static rows either.
> You have two options:
> Option 1: lose all schema
> create table movies ( name string, column blob, value blob, primary
> key(name)) with compact storage.
> This method is not so hot we have not lost all our validators, and by the way
> you have to physically shutdown everything and rename files and recreate your
> schema if you want to inform cassandra that a current table should be
> compact. This could at very least be just a metadata change. Also you can not
> add column schema either.
> Option 2 Normalize (is even worse)
> create table movie (name String, description string, likestoday int,
> blacklisted int);
> create table movecredits( name string, role string, personname string,
> primary key(name,role) );
> create table movetags( name string, tag string, primary key (name,tag) );
> This is a terrible design, of the 4 key characteristics how cassandra data
> should be designed it fails 3:
> It does not:
> 1) Denormalize
> 2) Eliminate seeks
> 3) Design for read
> Why is Cassandra steering toward this course, by making a language that does
> not understand wide rows?
> So what can be done? My suggestions:
> Cassandra needs to lose the COMPACT STORAGE conversions. Each table needs a
> "virtual view" that is compact storage with no work to migrate data and
> recreate schemas. Every table should have a compact view for the schemaless,
> or a simple query hint like /*transposed*/ should make this change.
> Metadata should be definable by regex. For example, all columnes named "tag*"
> are of type string.
> CQL should have the column[slice_start] .. column[slice_end] operator from
> cql2.
> CQL should support current users, users should not have to
> switch between CQL versions, and possibly thrift, to work with wide rows. The
> language should work for them even if
> it not expressly designed for them. Some of these features are already part
> of cql2 so they should be carried over.
> Also what needs to not happen is someone to make a hand waiving statement
> like "Once we have collection types we will not need wide rows". This request
> is to satisfy current users of cassandra not future ones or theoretical ones.
> Solutions should not involve physically migrating data in any way, they
> should not involve telling someone to do something they are already doing
> much differently. The suggestions should revolve around making the query
> language work well with existing data.
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