Thanks so much, Micah! I think you are using the right setting, but maybe it is possible the > strings are still exceeding the threshold (perhaps increasing it by 50x or > more to verify)
I'm glad I was looking at the right setting for dictionary size. I just tried it out with 10x, 50x, and even total file size, though, and still am not seeing a dictionary get created. Is it possible it's bounded by file page size or some other layout option that I need to bump as well? I haven't seen my discussion during my time in the community but maybe it > was discussed in the past. I think the main challenge here is that pages > are either dictionary encoded or not. I'd guess to make this practical > there would need to be a new hybrid page type, which I think it might be an > interesting idea but quite a bit of work. Additionally, one would likely > need heuristics for when to potentially use the new mode versus a complete > fallback. > Got it, thanks for the explanation! It does seem like a huge amount of work Best, Claire On Thu, Sep 14, 2023 at 5:16 PM Micah Kornfield <emkornfi...@gmail.com> wrote: > > > > - What's the heuristic for Parquet dictionary writing to succeed for a > > given column? > > > > https://github.com/apache/parquet-mr/blob/9b5a962df3007009a227ef421600197531f970a5/parquet-column/src/main/java/org/apache/parquet/column/values/dictionary/DictionaryValuesWriter.java#L117 > > > > - Is that heuristic configurable at all? > > > I think you are using the right setting, but maybe it is possible the > strings are still exceeding the threshold (perhaps increasing it by 50x or > more to verify) > > > > - For high-cardinality datasets, has the idea of a frequency-based > > dictionary encoding been explored? Say, if the data follows a certain > > statistical distribution, we can create a dictionary of the most frequent > > values only? > > I haven't seen my discussion during my time in the community but maybe it > was discussed in the past. I think the main challenge here is that pages > are either dictionary encoded or not. I'd guess to make this practical > there would need to be a new hybrid page type, which I think it might be an > interesting idea but quite a bit of work. Additionally, one would likely > need heuristics for when to potentially use the new mode versus a complete > fallback. > > Cheers, > Micah > > On Thu, Sep 14, 2023 at 12:07 PM Claire McGinty < > claire.d.mcgi...@gmail.com> > wrote: > > > Hi dev@, > > > > I'm running some benchmarking on Parquet read/write performance and have > a > > few questions about how dictionary encoding works under the hood. Let me > > know if there's a better channel for this :) > > > > My test case uses parquet-avro, where I'm writing a single file > containing > > 5 million records. Each record has a single column, an Avro String field > > (Parquet binary field). I ran two configurations of base setup: in the > > first case, the string field has 5,000 possible unique values. In the > > second case, it has 50,000 unique values. > > > > In the first case (5k unique values), I used parquet-tools to inspect the > > file metadata and found that a dictionary had been written: > > > > % parquet-tools meta testdata-case1.parquet > > > file schema: testdata.TestRecord > > > > > > > > > -------------------------------------------------------------------------------- > > > stringField: REQUIRED BINARY L:STRING R:0 D:0 > > > row group 1: RC:5000001 TS:18262874 OFFSET:4 > > > > > > > > > -------------------------------------------------------------------------------- > > > stringField: BINARY UNCOMPRESSED DO:4 FPO:38918 > SZ:8181452/8181452/1.00 > > > VC:5000001 ENC:BIT_PACKED,PLAIN_DICTIONARY ST:[min: 0, max: 999, > > num_nulls: > > > 0] > > > > > > But in the second case (50k unique values), parquet-tools shows that no > > dictionary gets created, and the file size is *much* bigger: > > > > % parquet-tools meta testdata-case2.parquet > > > file schema: testdata.TestRecord > > > > > > > > > -------------------------------------------------------------------------------- > > > stringField: REQUIRED BINARY L:STRING R:0 D:0 > > > row group 1: RC:5000001 TS:18262874 OFFSET:4 > > > > > > > > > -------------------------------------------------------------------------------- > > > stringField: BINARY UNCOMPRESSED DO:0 FPO:4 SZ:43896278/43896278/1.00 > > > VC:5000001 ENC:PLAIN,BIT_PACKED ST:[min: 0, max: 9999, num_nulls: 0] > > > > > > (I created a gist of my test reproduction here > > <https://gist.github.com/clairemcginty/c3c0be85f51bc23db45a75e8d8a18806 > >.) > > > > Based on this, I'm guessing there's some tip-over point after which > Parquet > > will give up on writing a dictionary for a given column? After reading > > the Configuration > > docs > > < > https://github.com/apache/parquet-mr/blob/master/parquet-hadoop/README.md > > >, > > I tried increasing the dictionary page size configuration 5x, with the > same > > result (no dictionary created). > > > > So to summarize, my questions are: > > > > - What's the heuristic for Parquet dictionary writing to succeed for a > > given column? > > - Is that heuristic configurable at all? > > - For high-cardinality datasets, has the idea of a frequency-based > > dictionary encoding been explored? Say, if the data follows a certain > > statistical distribution, we can create a dictionary of the most frequent > > values only? > > > > Thanks for your time! > > - Claire > > >
