Are you trying to add HLL UDAF for hive? If so recent versions of Hive already has an implementation of HLL++ which does not need bitset. https://github.com/apache/hive/tree/master/standalone-metastore/src/main/java/org/apache/hadoop/hive/common/ndv/hll
Also the bloom filter implementation in hive uses the raw bitset backed by long[] which seems to be fastest. https://github.com/apache/hive/blob/master/storage-api/src/java/org/apache/hive/common/util/BloomFilter.java#L330 Thanks Prasanth On Dec 11, 2017, at 8:25 PM, Nitin Vijayvargiya <nitinvija...@gmail.com<mailto:nitinvija...@gmail.com>> wrote: Hi Prasanth, Thanks, that was exactly what I was looking for. My main concern is speed, so I tried going with the brickhouse implementation of HLL+, and ended up having to make minor modifications to the code in order to have it run. My only concern is that the precision check tests don't always pass. Given that I had to comment out the @Ignore("not ready yet") over the test class, I'm unsure whether this code is safe to use. Anyone else had this problem? Thanks, Nitin On Mon, Dec 11, 2017 5:20 PM, Prasanth Jayachandran pjayachand...@hortonworks.com<mailto:pjayachand...@hortonworks.com> wrote: I did performance benchmark for roaring bitmaps when I added bloomfilters (hyperloglog also shares the same bitset impl) to Orc and Hive. I found that roaring bitmap is good at compression at the cost of speed. In a JMH benchmark, observed around ~10x slowdown during insert and probe when using roaring bitmap vs the raw bitset (long array without compression). So it essentially boils down to speed vs space tradeoff. Thanks Prasanth On Dec 11, 2017, at 3:58 PM, Nitin Vijayvargiya <nitinvija...@gmail.com<mailto:nitinvija...@gmail.com>> wrote: Hi David, Thanks for the response. Yea, bloom filters are mostly for existential checks. I'm looking for a way to preprocess data, and then perform operations like union/intersection between them to find counts. Example: Number of distinct users visiting website A over the last 5 days (union), intersected with the number of distinct visitors visiting website B over the last 10 days (union). Hyperloglog is the right tool for this, but if someone has done performance benchmarking between HLL and Roaring BitMap, it would save me a lot of time. Thanks, Nitin On Fri, Dec 8, 2017 7:08 PM, David Capwell dcapw...@gmail.com<mailto:dcapw...@gmail.com> wrote: Think bloom filter that's more dynamic. It works well when cardinality is low, but grows quickly to out cost bloom filter as cardinality grows. This data structure supports existence queries, but your email sounds like you want count. If so not really the best fit. On Dec 8, 2017 5:00 PM, "Nitin Vijayvargiya" <nitinvija...@gmail.com<mailto:nitinvija...@gmail.com>> wrote: Hi all, I'm working on speeding up distinct count calculations, and it looks like roaring bitmaps (RB) is the newest and meanest way for set operations. Anyone here have experience with them? How was the performance compared to hyperloglog and EWAH? A quick google search showed me that it's easier to find UDF implementations of hyperloglog in presto and hive, but if the hype is real, it might be worth spending the time to incorporate RB. Also, if anyone can point me to reliable implementations of UDFs using RB, I would love to check it out and test it myself =) Happy Holidays! Nitin
