Gautam, you need to have the jmh-core libraries available to run. I validated that PR, so I'm guessing I had it configured in my environment.
I assume there's a way to make that available within gradle, so I'll take a look. On Fri, Jul 26, 2019 at 2:52 PM Gautam <gautamkows...@gmail.com> wrote: > This fails on master too btw. Just wondering if i'm doing something wrong > trying to run this. > > On Fri, Jul 26, 2019 at 2:24 PM Gautam <gautamkows...@gmail.com> wrote: > >> I'v been trying to run the jmh benchmarks bundled within the project. I'v >> been running into issues with that .. have other hit this? Am I running >> these incorrectly? >> >> >> bash-3.2$ ./gradlew :iceberg-spark:jmh >> -PjmhIncludeRegex=IcebergSourceFlatParquetDataFilterBenchmark >> -PjmhOutputPath=benchmark/iceberg-source-flat-parquet-data-filter-benchmark-result.txt >> .. >> ... >> > Task :iceberg-spark:jmhCompileGeneratedClasses FAILED >> error: plug-in not found: ErrorProne >> >> FAILURE: Build failed with an exception. >> >> >> >> Is there a config/plugin I need to add to build.gradle? >> >> >> >> >> >> >> >> >> On Wed, Jul 24, 2019 at 2:03 PM Ryan Blue <rb...@netflix.com> wrote: >> >>> Thanks Gautam! >>> >>> We'll start taking a look at your code. What do you think about creating >>> a branch in the Iceberg repository where we can work on improving it >>> together, before merging it into master? >>> >>> Also, you mentioned performance comparisons. Do you have any early >>> results to share? >>> >>> rb >>> >>> On Tue, Jul 23, 2019 at 3:40 PM Gautam <gautamkows...@gmail.com> wrote: >>> >>>> Hello Folks, >>>> >>>> I have checked in a WIP branch [1] with a working version of Vectorized >>>> reads for Iceberg reader. Here's the diff [2]. >>>> >>>> *Implementation Notes:* >>>> - Iceberg's Reader adds a `SupportsScanColumnarBatch` mixin to >>>> instruct the DataSourceV2ScanExec to use `planBatchPartitions()` instead of >>>> the usual `planInputPartitions()`. It returns instances of `ColumnarBatch` >>>> on each iteration. >>>> - `ArrowSchemaUtil` contains Iceberg to Arrow type conversion. This >>>> was copied from [3] . Added by @Daniel Weeks <dwe...@netflix.com> . >>>> Thanks for that! >>>> - `VectorizedParquetValueReaders` contains ParquetValueReaders used >>>> for reading/decoding the Parquet rowgroups (aka pagestores as referred to >>>> in the code) >>>> - `VectorizedSparkParquetReaders` contains the visitor implementations >>>> to map Parquet types to appropriate value readers. I implemented the struct >>>> visitor so that the root schema can be mapped properly. This has the added >>>> benefit of vectorization support for structs, so yay! >>>> - For the initial version the value readers read an entire row group >>>> into a single Arrow Field Vector. this i'd imagine will require tuning for >>>> right batch sizing but i'v gone with one batch per rowgroup for now. >>>> - Arrow Field Vectors are wrapped using `ArrowColumnVector` which is >>>> Spark's ColumnVector implementation backed by Arrow. This is the first >>>> contact point between Spark and Arrow interfaces. >>>> - ArrowColumnVectors are stitched together into a `ColumnarBatch` by >>>> `ColumnarBatchReader` . This is my replacement for `InternalRowReader` >>>> which maps Structs to Columnar Batches. This allows us to have nested >>>> structs where each level of nesting would be a nested columnar batch. Lemme >>>> know what you think of this approach. >>>> - I'v added value readers for all supported primitive types listed in >>>> `AvroDataTest`. There's a corresponding test for vectorized reader under >>>> `TestSparkParquetVectorizedReader` >>>> - I haven't fixed all the Checkstyle errors so you will have to turn >>>> checkstyle off in build.gradle. Also skip tests while building.. sorry! :-( >>>> >>>> *P.S*. There's some unused code under ArrowReader.java. Ignore this as >>>> it's not used. This was from my previous impl of Vectorization. I'v kept it >>>> around to compare performance. >>>> >>>> Lemme know what folks think of the approach. I'm getting this working >>>> for our scale test benchmark and will report back with numbers. Feel free >>>> to run your own benchmarks and share. >>>> >>>> Cheers, >>>> -Gautam. >>>> >>>> >>>> >>>> >>>> [1] - >>>> https://github.com/prodeezy/incubator-iceberg/tree/issue-9-support-arrow-based-reading-WIP >>>> [2] - >>>> https://github.com/apache/incubator-iceberg/compare/master...prodeezy:issue-9-support-arrow-based-reading-WIP >>>> [3] - >>>> https://github.com/apache/incubator-iceberg/blob/72e3485510e9cbec05dd30e2e7ce5d03071f400d/core/src/main/java/org/apache/iceberg/arrow/ArrowSchemaUtil.java >>>> >>>> >>>> On Mon, Jul 22, 2019 at 2:33 PM Gautam <gautamkows...@gmail.com> wrote: >>>> >>>>> Will do. Doing a bit of housekeeping on the code and also adding more >>>>> primitive type support. >>>>> >>>>> On Mon, Jul 22, 2019 at 1:41 PM Matt Cheah <mch...@palantir.com> >>>>> wrote: >>>>> >>>>>> Would it be possible to put the work in progress code in open source? >>>>>> >>>>>> >>>>>> >>>>>> *From: *Gautam <gautamkows...@gmail.com> >>>>>> *Reply-To: *"dev@iceberg.apache.org" <dev@iceberg.apache.org> >>>>>> *Date: *Monday, July 22, 2019 at 9:46 AM >>>>>> *To: *Daniel Weeks <dwe...@netflix.com> >>>>>> *Cc: *Ryan Blue <rb...@netflix.com>, Iceberg Dev List < >>>>>> dev@iceberg.apache.org> >>>>>> *Subject: *Re: Approaching Vectorized Reading in Iceberg .. >>>>>> >>>>>> >>>>>> >>>>>> That would be great! >>>>>> >>>>>> >>>>>> >>>>>> On Mon, Jul 22, 2019 at 9:12 AM Daniel Weeks <dwe...@netflix.com> >>>>>> wrote: >>>>>> >>>>>> Hey Gautam, >>>>>> >>>>>> >>>>>> >>>>>> We also have a couple people looking into vectorized reading (into >>>>>> Arrow memory). I think it would be good for us to get together and see >>>>>> if >>>>>> we can collaborate on a common approach for this. >>>>>> >>>>>> >>>>>> >>>>>> I'll reach out directly and see if we can get together. >>>>>> >>>>>> >>>>>> >>>>>> -Dan >>>>>> >>>>>> >>>>>> >>>>>> On Sun, Jul 21, 2019 at 10:35 PM Gautam <gautamkows...@gmail.com> >>>>>> wrote: >>>>>> >>>>>> Figured this out. I'm returning ColumnarBatch iterator directly >>>>>> without projection with schema set appropriately in `readSchema() `.. the >>>>>> empty result was due to valuesRead not being set correctly on >>>>>> FileIterator. >>>>>> Did that and things are working. Will circle back with numbers soon. >>>>>> >>>>>> >>>>>> >>>>>> On Fri, Jul 19, 2019 at 5:22 PM Gautam <gautamkows...@gmail.com> >>>>>> wrote: >>>>>> >>>>>> Hey Guys, >>>>>> >>>>>> Sorry bout the delay on this. Just got back on getting a >>>>>> basic working implementation in Iceberg for Vectorization on primitive >>>>>> types. >>>>>> >>>>>> >>>>>> >>>>>> *Here's what I have so far : * >>>>>> >>>>>> >>>>>> >>>>>> I have added `ParquetValueReader` implementations for some basic >>>>>> primitive types that build the respective Arrow Vector (`ValueVector`) >>>>>> viz. >>>>>> `IntVector` for int, `VarCharVector` for strings and so on. Underneath >>>>>> each >>>>>> value vector reader there are column iterators that read from the parquet >>>>>> pagestores (rowgroups) in chunks. These `ValueVector-s` are lined up as >>>>>> `ArrowColumnVector`-s (which is ColumnVector wrapper backed by Arrow) and >>>>>> stitched together using a `ColumnarBatchReader` (which as the name >>>>>> suggests >>>>>> wraps ColumnarBatches in the iterator) I'v verified that these pieces >>>>>> work properly with the underlying interfaces. I'v also made changes to >>>>>> Iceberg's `Reader` to implement `planBatchPartitions()` (to add the >>>>>> `SupportsScanColumnarBatch` mixin to the reader). So the reader now >>>>>> expects ColumnarBatch instances (instead of InternalRow). The query >>>>>> planning runtime works fine with these changes. >>>>>> >>>>>> >>>>>> >>>>>> Although it fails during query execution, the bit it's currently >>>>>> failing at is this line of code : >>>>>> https://github.com/apache/incubator-iceberg/blob/master/spark/src/main/java/org/apache/iceberg/spark/source/Reader.java#L414 >>>>>> [github.com] >>>>>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache_incubator-2Diceberg_blob_master_spark_src_main_java_org_apache_iceberg_spark_source_Reader.java-23L414&d=DwMFaQ&c=izlc9mHr637UR4lpLEZLFFS3Vn2UXBrZ4tFb6oOnmz8&r=hzwIMNQ9E99EMYGuqHI0kXhVbvX3nU3OSDadUnJxjAs&m=UW1Nb5KZOPeIqsjzFnKhGQaxYHT_wAI_2PvgFUlfAoY&s=7wzoBoRwCjQjgamnHukQSe0wiATMnGbYhfJQpXfSMks&e=> >>>>>> >>>>>> >>>>>> >>>>>> This code, I think, tries to apply the iterator's schema projection >>>>>> on the InternalRow instances. This seems to be tightly coupled to >>>>>> InternalRow as Spark's catalyst expressions have implemented the >>>>>> UnsafeProjection for InternalRow only. If I take this out and just return >>>>>> the `Iterator<ColumnarBatch>` iterator I built it returns empty result on >>>>>> the client. I'm guessing this is coz Spark is unaware of the iterator's >>>>>> schema? There's a Todo in the code that says "*remove the projection >>>>>> by reporting the iterator's schema back to Spark*". Is there a >>>>>> simple way to communicate that to Spark for my new iterator? Any pointers >>>>>> on how to get around this? >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> Thanks and Regards, >>>>>> >>>>>> -Gautam. >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> On Fri, Jun 14, 2019 at 4:22 PM Ryan Blue <rb...@netflix.com> wrote: >>>>>> >>>>>> Replies inline. >>>>>> >>>>>> >>>>>> >>>>>> On Fri, Jun 14, 2019 at 1:11 AM Gautam <gautamkows...@gmail.com> >>>>>> wrote: >>>>>> >>>>>> Thanks for responding Ryan, >>>>>> >>>>>> >>>>>> >>>>>> Couple of follow up questions on ParquetValueReader for Arrow.. >>>>>> >>>>>> >>>>>> >>>>>> I'd like to start with testing Arrow out with readers for primitive >>>>>> type and incrementally add in Struct/Array support, also ArrowWriter [1] >>>>>> currently doesn't have converters for map type. How can I default these >>>>>> types to regular materialization whilst supporting Arrow based support >>>>>> for >>>>>> primitives? >>>>>> >>>>>> >>>>>> >>>>>> We should look at what Spark does to handle maps. >>>>>> >>>>>> >>>>>> >>>>>> I think we should get the prototype working with test cases that >>>>>> don't have maps, structs, or lists. Just getting primitives working is a >>>>>> good start and just won't hit these problems. >>>>>> >>>>>> >>>>>> >>>>>> Lemme know if this makes sense... >>>>>> >>>>>> >>>>>> >>>>>> - I extend PrimitiveReader (for Arrow) that loads primitive types >>>>>> into ArrowColumnVectors of corresponding column types by iterating over >>>>>> underlying ColumnIterator *n times*, where n is size of batch. >>>>>> >>>>>> >>>>>> >>>>>> Sounds good to me. I'm not sure about extending vs wrapping because >>>>>> I'm not too familiar with the Arrow APIs. >>>>>> >>>>>> >>>>>> >>>>>> - Reader.newParquetIterable() maps primitive column types to the >>>>>> newly added ArrowParquetValueReader but for other types (nested types, >>>>>> etc.) uses current *InternalRow* based ValueReaders >>>>>> >>>>>> >>>>>> >>>>>> Sounds good for primitives, but I would just leave the nested types >>>>>> un-implemented for now. >>>>>> >>>>>> >>>>>> >>>>>> - Stitch the columns vectors together to create ColumnarBatch, (Since >>>>>> *SupportsScanColumnarBatch* mixin currently expects this ) .. >>>>>> *although* *I'm a bit lost on how the stitching of columns happens >>>>>> currently*? .. and how the ArrowColumnVectors could be stitched >>>>>> alongside regular columns that don't have arrow based support ? >>>>>> >>>>>> >>>>>> >>>>>> I don't think that you can mix regular columns and Arrow columns. It >>>>>> has to be all one or the other. That's why it's easier to start with >>>>>> primitives, then add structs, then lists, and finally maps. >>>>>> >>>>>> >>>>>> >>>>>> - Reader returns readTasks as *InputPartition<*ColumnarBatch*> *so >>>>>> that DataSourceV2ScanExec starts using ColumnarBatch scans >>>>>> >>>>>> >>>>>> >>>>>> We will probably need two paths. One for columnar batches and one for >>>>>> row-based reads. That doesn't need to be done right away and what you >>>>>> already have in your working copy makes sense as a start. >>>>>> >>>>>> >>>>>> >>>>>> That's a lot of questions! :-) but hope i'm making sense. >>>>>> >>>>>> >>>>>> >>>>>> -Gautam. >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> [1] - >>>>>> https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/arrow/ArrowWriter.scala >>>>>> [github.com] >>>>>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_apache_spark_blob_master_sql_core_src_main_scala_org_apache_spark_sql_execution_arrow_ArrowWriter.scala&d=DwMFaQ&c=izlc9mHr637UR4lpLEZLFFS3Vn2UXBrZ4tFb6oOnmz8&r=hzwIMNQ9E99EMYGuqHI0kXhVbvX3nU3OSDadUnJxjAs&m=UW1Nb5KZOPeIqsjzFnKhGQaxYHT_wAI_2PvgFUlfAoY&s=8yzJh2S49rbuM06dC5Sy-yMECClqEeLS7tpg45BmDN4&e=> >>>>>> >>>>>> >>>>>> >>>>>> -- >>>>>> >>>>>> Ryan Blue >>>>>> >>>>>> Software Engineer >>>>>> >>>>>> Netflix >>>>>> >>>>>> >>> >>> -- >>> Ryan Blue >>> Software Engineer >>> Netflix >>> >>
