JCC-H: Adding Join Crossing Correlations with Skew to TPC-H

Boncz, Peter; Anatiotis, Angelos-Christos; Kläbe, Steffen

doi:10.1007/978-3-319-72401-0_8

Cited by 10 publications

(3 citation statements)

References 8 publications

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“…In the Join Order Benchmark [22], the RJ performed worse because it is string-processing heavy. 11 JCC-H [8] provides a more realistic drop-in replacement for TPC-H with skew. It puts even more pressure on the radix join.…”

Section: Discussionmentioning

confidence: 99%

To Partition, or Not to Partition, That is the Join Question in a Real System

Bandle

Giceva

Neumann

2021

Proceedings of the 2021 International Conference on Management of Data

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An efficient implementation of a hash join has been a highly researched problem for decades. Recently, the radix join has been shown to have superior performance over the alternatives (e.g., the non-partitioned hash join), albeit on synthetic microbenchmarks. Therefore, it is unclear whether one can simply replace the hash join in an RDBMS or use the radix join as a performance booster for selected queries. If the latter, it is still unknown when one should rely on the radix join to improve performance.In this paper, we address these questions, show how to integrate the radix join in Umbra, a code-generating DBMS, and make it competitive for selective queries by introducing a Bloom-filter based semi-join reducer. We have evaluated how well it runs when used in queries from more representative workloads like TPC-H. Surprisingly, the radix join brings a noticeable improvement in only one out of all 59 joins in TPC-H. Thus, with an extensive range of microbenchmarks, we have isolated the effects of the most important workload factors and synthesized the range of values where partitioning the data for the radix join pays off. Our analysis shows that the benefit of data partitioning quickly diminishes as soon as we deviate from the optimal parameters, and even late materialization rarely helps in real workloads. We thus, conclude that integrating the radix join within a code-generating database rarely justifies the increase in code and optimizer complexity and advise against it for processing real-world workloads. CCS CONCEPTS• Information systems → Main memory engines; Join algorithms.

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Section: Discussionmentioning

confidence: 99%

To Partition, or Not to Partition, That is the Join Question in a Real System

Bandle

Giceva

Neumann

2021

Proceedings of the 2021 International Conference on Management of Data

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“…The JCC-H [9] benchmark demonstrates these problems, where there are five populous orders that have very many lineitems. When we groupjoin these orders with the lineitem table, the index based execution is essentially singlethreaded, while the memoizing and eager right execution execute on all available cores.…”

Section: Using Indexes For Groupjoinsmentioning

confidence: 99%

Practical planning and execution of groupjoin and nested aggregates

2022

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Groupjoins combine execution of a join and a subsequent group-by. They are common in analytical queries and occur in about "Equation missing" of the queries in TPC-H and TPC-DS. While they were originally invented to improve performance, efficient parallel execution of groupjoins can be limited by contention in many-core systems. Efficient implementations of groupjoins are highly desirable, as groupjoins are not only used to fuse group-by and join, but are also useful to efficiently execute nested aggregates. For these, the query optimizer needs to reason over the result of aggregation to optimally schedule it. Traditional systems quickly reach their limits of selectivity and cardinality estimations over computed columns and often treat group-by as an optimization barrier. In this paper, we present techniques to efficiently estimate, plan, and execute groupjoins and nested aggregates. We propose four novel techniques, aggregate estimates to predict the result distributions of aggregates, parallel groupjoin execution for scalable execution of groupjoins, index groupjoins, and a greedy eager aggregation optimization technique that introduces nested preaggregations to significantly improve execution plans. The resulting system has improved estimates, better execution plans, and a contention-free evaluation of groupjoins, which speeds up TPC-H and TPC-DS queries significantly.

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“…It has been noted that synthetic benchmarks like TPC-H do not capture all relevant aspects of real workloads [6], [9]. Recently, a workload study was published [31] based on the Tableau Public 1 Business Intelligence (BI) free cloud service.…”

Section: B Public Bi Benchmarkmentioning

confidence: 99%

Efficient Query Processing with Optimistically Compressed Hash Tables & Strings in the USSR

Gubner

Leis

Boncz

2020

2020 IEEE 36th International Conference on Data Engineering (ICDE)

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Modern query engines rely heavily on hash tables for query processing. Overall query performance and memory footprint is often determined by how hash tables and the tuples within them are represented. In this work, we propose three complementary techniques to improve this representation: Domain-Guided Prefix Suppression bit-packs keys and values tightly to reduce hash table record width. Optimistic Splitting decomposes values (and operations on them) into (operations on) frequently-accessed and infrequently-accessed value slices. By removing the infrequently-accessed value slices from the hash table record, it improves cache locality. The Unique Strings Selfaligned Region (USSR) accelerates handling frequently-occurring strings, which are very common in real-world data sets, by creating an on-the-fly dictionary of the most frequent strings. This allows executing many string operations with integer logic and reduces memory pressure. We integrated these techniques into Vectorwise. On the TPC-H benchmark, our approach reduces peak memory consumption by 2-4× and improves performance by up to 1.5×. On a real-world BI workload, we measured a 2× improvement in performance and in micro-benchmarks we observed speedups of up to 25×.

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JCC-H: Adding Join Crossing Correlations with Skew to TPC-H

Cited by 10 publications

References 8 publications

To Partition, or Not to Partition, That is the Join Question in a Real System

To Partition, or Not to Partition, That is the Join Question in a Real System

Practical planning and execution of groupjoin and nested aggregates

Efficient Query Processing with Optimistically Compressed Hash Tables & Strings in the USSR

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