cassandra-2.0

I'm using spark with cassandra, and i hava a JavaRDD<String> of clients. And for each client, i want to select from cassandra his Interactions like this : avaPairRDD<String, List<InteractionByMonthAndCustomer>> a = client.mapToPair(new PairFunction<String, String, List<InteractionByMonthAndCustomer>>() { @Override public Tuple2<String, List<InteractionByMonthAndCustomer>> call(String s) throws Exception { List<InteractionByMonthAndCustomer> b = javaFunctions(sc) .cassandraTable(CASSANDRA_SCHEMA, "interaction_by_month_customer") .where("ctid =?", s) .map(new Function<CassandraRow,

How are static columns stored internally in cassandra? Can someone please post an example discussing the design implementation of static column in cassandra? Why don't we take a look at the structure of a table with static columns on disk and find out? cqlsh:test> CREATE TABLE test (k int, v int, s int static, d int, PRIMARY KEY(k,v)) cqlsh:test> INSERT INTO test (k, v, s, d) VALUES ( 1, 1 ,20, 1 ); cqlsh:test> INSERT INTO test (k, v, s, d) VALUES ( 1, 3 ,21, 2 ); cqlsh:test> INSERT INTO test (k, v, s, d) VALUES ( 1, 2 ,21, 2 ); Exit out of C* and run nodetool flush to make our sstables. Run

What do you mean by Batch Statements are atomic in cassandra? Docs are a bit confusing in nature to be precise. Does it mean that queries are atomic across nodes in cluster? Say,for example, i have a batch with 100 queries. If the 40th query in batch fails, what happens to the 39 queries executed in the batch? I understand that there is a batchlog created under the hood and it will take care of the consistency for partial batches. Does it remove the rest of the 39 entries and provide the required atomic nature of batch queries. In MYSQL, we set autocommit to false and hence we can rollback.

Writing data to Cassandra without causing it to create tombstones are vital in our case, due to the amount of data and speed. Currently we have only written a row once, and then never had the need to update the row again, only fetch the data again. Now there has been a case, where we actually need to write data, and then complete it with more data, that is finished after awhile. It can be made by either; overwrite all of the data in a row again using INSERT (all data is available), or performing an Update only on the new data. What is the best way to do it, bear in mind of the speed and not

What is the canonical way to model many-to-many relations with CQL3 ? Let's say I have to tables CREATE TABLE actor ( id text PRIMARY KEY, given text, surname text, ) CREATE TABLE fan ( id text PRIMARY KEY, given text, surname text, ) and I'd like to model the fact that an actor can have many fan and each fan can like many actors. The first idea that came to my my was to use sets , like in the following (and the other way around for fans): CREATE TABLE actor ( id text PRIMARY KEY, given text, surname text, fans set<text> ) <similarly for fan> but it seems they are meant for small sets, and I

Cassandra newbie question. I'm collecting some data from a social networking site using REST calls. So I end up with the data coming back in JSON format. The JSON is only one of the columns in my table. I'm trying to figure out what the "best practice" is for storing the JSON string. First I thought of using the map type, but the JSON contains a mix of strings, numerical types, etc. It doesn't seem like I can declare wildcard types for the map key/value. The JSON string can be quite large, probably over 10KB in size. I could potentially store it as a string, but it seems like that would be

I am trying to insert a simple row into the table. Can someone point out what is happening here ? CREATE TABLE recommendation_engine_poc.user_by_category ( game_category text, customer_id text, amount double, game_date timestamp, PRIMARY KEY (game_category, customer_id) ) WITH CLUSTERING ORDER BY (customer_id ASC) AND bloom_filter_fp_chance = 0.01 AND caching = '{"keys":"ALL", "rows_per_partition":"NONE"}' AND comment = '' AND compaction = {'class': 'org.apache.cassandra.db.compaction.SizeTieredCompactionStrategy'} AND compression = {'sstable_compression': 'org.apache.cassandra.io.compress