I'm evaluating using Cassandra as a binary object store. In my experiments I'm not getting good enough read throughput for single queries to single nodes. Even on a MacBook Pro 15 2018 reading e.g. a 128 MiB blob in 64KiB chunks with the Cassandra C++ driver from a single node on the loopback interface takes about 300ms. I was hoping I could saturate a 10 GiB port on a fast enough server with single requests for large blobs. Are there any C++ driver, Cassandra or Java VM tuning options that could improve read throughput in this scenario?
The blob table has the following schema:
CREATE TABLE blobs.blob ( id uuid, chunk_id int, blob_size int, creation_time timestamp, data blob, data_type text, hash blob, info text, update_time timestamp, PRIMARY KEY (id, chunk_id) ) WITH CLUSTERING ORDER BY (chunk_id ASC) AND bloom_filter_fp_chance = 0.01 AND caching = {'keys': 'ALL', 'rows_per_partition': 'ALL'} AND comment = '' AND compaction = {'class': 'org.apache.cassandra.db.compaction.SizeTieredCompactionStrategy', 'max_threshold': '32', 'min_threshold': '4'} AND compression = {'enabled': 'false'} AND crc_check_chance = 0.0 AND dclocal_read_repair_chance = 0.1 AND default_time_to_live = 0 AND gc_grace_seconds = 864000 AND max_index_interval = 2048 AND memtable_flush_period_in_ms = 0 AND min_index_interval = 128 AND read_repair_chance = 0.0 AND speculative_retry = '99PERCENTILE';