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3 Commits
| Author | SHA1 | Message | Date | |
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e6c930a38f |
IMPALA-9747: More fine-grained codegen for text file scanners
Currently if the materialization of any column cannot be codegen'd
because its type is unsupported (e.g. CHAR(N)), the whole codegen is
cancelled for the text scanner.
This commit adds the function TextConverter::SupportsCodegenWriteSlot
that returns whether the given ColumnType is supported. If the type is
not supported, HdfsScanner codegens code that calls the interpreted
version instead of failing codegen. For other columns codegen is used as
usually.
Benchmarks:
Copied and modified a TPCH table with scale factor 5 to add a CHAR
column to it::
USE tpch5;
CREATE TABLE IF NOT EXISTS lineitem_char AS
SELECT *, CAST(l_shipdate AS CHAR(10)) l_shipdate_char
FROM lineitem;
Run the following query 100 times after one warm-up run with and
without this change:
SELECT *
FROM tpch5.lineitem_char
WHERE
l_partkey BETWEEN 500 AND 500000 AND
l_linestatus = 'F' AND
l_quantity < 35 AND
l_extendedprice BETWEEN 2000 AND 8000 AND
l_discount > 0 AND
l_tax BETWEEN 0.04 AND 0.06 AND
l_returnflag IN ('A', 'N') AND
l_shipdate_char < '1996-06-20'
ORDER BY l_shipdate_char
LIMIT 10;
Without this commit: mean: 2.92, standard deviation: 0.13.
With this commit: mean: 2.21, standard deviation: 0.072.
Testing:
The interesting cases regarding char are covered in
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d4648e87b4 |
IMPALA-4356,IMPALA-7331: codegen all ScalarExprs
Based on initial draft patch by Pooja Nilangekar.
Codegen'd expressions can be executed in two ways - either by
being called directly from a fully codegend function, or from
interpreted code via a function pointer (previously
ScalarFnCall::scalar_fn_wrapper_).
This change moves the function pointer from ScalarFnCall to its
base class ScalarExpr, so the full expr tree can be codegen'd, not
just the ScalarFnCall subtrees. The key refactoring and improvements
are:
* ScalarExpr::Get*Val() switches between interpreted and the codegen'd
function pointer code paths in an inline function, avoiding a
virtual function call to ScalarFnCal::Get*Val().
* Boilerplate logic is moved to ScalarExpr::GetCodegendComputeFn(),
which calls a virtual function GetCodegenComputeFnImpl().
* ScalarFnCall's logic for deciding whether to interpret or codegen is
better abstracted and exposed to ScalarExpr as IsInterpretable()
and ShouldCodegen() methods.
* The ScalarExpr::codegend_compute_fn_ function pointer is only
populated for expressions that are "codegen entry points". These
include the roots of expr trees and non-root expressions
where the parent expression calls Get*Val() from the
pseudo-codegend GetCodegendComputeFnWrapper().
* ScalarFnCall is always initialised for interpreted execution.
Otherwise the function pointer is needed for non-root expressions,
e.g. to support ScalarExprEvaluator::GetConstantVal().
* Latent bugs/gaps for codegen of CollectionVal are fixed. CollectionVal
is modified to use the StringVal memory layout to allow code sharing
with StringVal. These fixes allowed simplification of
IsNotEmptyPredicate codegen (from IMPALA-7657).
I chose to tackle two problems in one change - adding support for
generating codegen'd function pointers for all ScalarExprs, and adding
the "entry point" concept - to avoid a blow-up in the number of
codegen'd entry points that could lead to longer codegen times and/or
worse code because of inlining changes.
IMPALA-7331 (CHAR codegen support functions) is also fixed because
it was simpler to enable CHAR codegen within ScalarExpr than to carry
forward the exiting CHAR workarounds from ScalarFnCall. The
CHAR-specific codegen support required in the scalar expr subsystem is
very limited. StringVal intermediates are used everywhere. Only
SlotRef actually operates on the different tuple layout, and the
required codegen support for SlotRef already exists for UDA
intermediates anyway.
Testing:
* Ran exhaustive tests.
Perf:
* Ran a basic insert benchmark, which went from 10.1s to 7.6s
create table foo stored as parquet as
select case when l_orderkey % 2 = 0 then 'aaa' else 'bbb' end
from tpch30_parquet.lineitem;
* Ran a basic CHAR expr test:
set num_nodes=1;
set mt_dop=1;
select count(*) from lineitem
where cast(l_linestatus as CHAR(2)) = 'O ' and
cast(l_returnflag as CHAR(2)) = 'N '
The time spent in the scan went from 520ms to 220ms.
* Added perf regression test to tpcds-insert, similar to the manual
benchmark.
* Ran single-node TPC-H with large and small scale factors, to estimate
impact on execution perf and query startup time, respectively.
+----------+-----------------------+---------+------------+------------+----------------+
| Workload | File Format | Avg (s) | Delta(Avg) | GeoMean(s) | Delta(GeoMean) |
+----------+-----------------------+---------+------------+------------+----------------+
| TPCH(30) | parquet / none / none | 6.84 | -0.18% | 4.49 | -0.31% |
+----------+-----------------------+---------+------------+------------+----------------+
+----------+----------+-----------------------+--------+-------------+------------+-----------+----------------+-------+----------------+---------+--------+
| Workload | Query | File Format | Avg(s) | Base Avg(s) | Delta(Avg) | StdDev(%) | Base StdDev(%) | Iters | Median Diff(%) | MW Zval | Tval |
+----------+----------+-----------------------+--------+-------------+------------+-----------+----------------+-------+----------------+---------+--------+
| TPCH(30) | TPCH-Q20 | parquet / none / none | 2.58 | 2.47 | +4.18% | 1.29% | 0.88% | 5 | +4.12% | 2.31 | 5.81 |
| TPCH(30) | TPCH-Q17 | parquet / none / none | 4.81 | 4.61 | +4.33% | 2.18% | 2.15% | 5 | +3.91% | 1.73 | 3.09 |
| TPCH(30) | TPCH-Q21 | parquet / none / none | 26.45 | 26.16 | +1.09% | 0.37% | 0.50% | 5 | +1.36% | 2.02 | 3.94 |
| TPCH(30) | TPCH-Q9 | parquet / none / none | 15.92 | 15.75 | +1.09% | 2.87% | 1.65% | 5 | +0.88% | 0.29 | 0.73 |
| TPCH(30) | TPCH-Q12 | parquet / none / none | 2.38 | 2.35 | +1.12% | 1.64% | 1.11% | 5 | +0.80% | 1.15 | 1.26 |
| TPCH(30) | TPCH-Q14 | parquet / none / none | 2.94 | 2.91 | +1.13% | 7.68% | 5.37% | 5 | -0.34% | -0.29 | 0.27 |
| TPCH(30) | TPCH-Q18 | parquet / none / none | 18.10 | 18.02 | +0.42% | 2.70% | 0.56% | 5 | +0.28% | 0.29 | 0.34 |
| TPCH(30) | TPCH-Q8 | parquet / none / none | 4.72 | 4.72 | -0.04% | 1.20% | 1.65% | 5 | +0.05% | 0.00 | -0.04 |
| TPCH(30) | TPCH-Q19 | parquet / none / none | 3.92 | 3.93 | -0.26% | 1.08% | 2.36% | 5 | +0.20% | 0.58 | -0.23 |
| TPCH(30) | TPCH-Q6 | parquet / none / none | 1.27 | 1.27 | -0.28% | 0.22% | 0.88% | 5 | +0.09% | 0.29 | -0.68 |
| TPCH(30) | TPCH-Q16 | parquet / none / none | 2.64 | 2.65 | -0.45% | 1.65% | 0.65% | 5 | -0.24% | -0.58 | -0.57 |
| TPCH(30) | TPCH-Q22 | parquet / none / none | 3.10 | 3.13 | -0.76% | 1.47% | 1.12% | 5 | -0.21% | -0.29 | -0.93 |
| TPCH(30) | TPCH-Q2 | parquet / none / none | 1.20 | 1.21 | -0.80% | 2.26% | 2.47% | 5 | -0.82% | -1.15 | -0.53 |
| TPCH(30) | TPCH-Q4 | parquet / none / none | 1.97 | 1.99 | -1.37% | 1.84% | 3.21% | 5 | -0.47% | -0.58 | -0.83 |
| TPCH(30) | TPCH-Q13 | parquet / none / none | 11.53 | 11.63 | -0.91% | 0.46% | 0.49% | 5 | -0.95% | -2.02 | -3.08 |
| TPCH(30) | TPCH-Q10 | parquet / none / none | 5.13 | 5.21 | -1.51% | 2.24% | 4.05% | 5 | -0.94% | -0.58 | -0.73 |
| TPCH(30) | TPCH-Q5 | parquet / none / none | 3.61 | 3.66 | -1.40% | 0.66% | 0.79% | 5 | -1.33% | -1.73 | -3.05 |
| TPCH(30) | TPCH-Q7 | parquet / none / none | 19.42 | 19.71 | -1.52% | 1.34% | 1.39% | 5 | -1.22% | -1.44 | -1.76 |
| TPCH(30) | TPCH-Q3 | parquet / none / none | 5.08 | 5.15 | -1.49% | 1.34% | 0.73% | 5 | -1.35% | -1.44 | -2.20 |
| TPCH(30) | TPCH-Q15 | parquet / none / none | 3.42 | 3.49 | -1.92% | 0.93% | 1.47% | 5 | -1.53% | -1.15 | -2.49 |
| TPCH(30) | TPCH-Q11 | parquet / none / none | 1.15 | 1.19 | -3.17% | 2.27% | 1.95% | 5 | -4.21% | -1.15 | -2.41 |
| TPCH(30) | TPCH-Q1 | parquet / none / none | 9.26 | 9.63 | -3.85% | 0.62% | 0.59% | 5 | -3.78% | -2.31 | -10.25 |
+----------+----------+-----------------------+--------+-------------+------------+-----------+----------------+-------+----------------+---------+--------+
Cluster Name: UNKNOWN
Lab Run Info: UNKNOWN
Impala Version: impalad version 3.2.0-SNAPSHOT RELEASE ()
Baseline Impala Version: impalad version 3.2.0-SNAPSHOT RELEASE (2019-03-19)
+----------+-----------------------+---------+------------+------------+----------------+
| Workload | File Format | Avg (s) | Delta(Avg) | GeoMean(s) | Delta(GeoMean) |
+----------+-----------------------+---------+------------+------------+----------------+
| TPCH(2) | parquet / none / none | 0.90 | -0.08% | 0.80 | -0.05% |
+----------+-----------------------+---------+------------+------------+----------------+
+----------+----------+-----------------------+--------+-------------+------------+-----------+----------------+-------+----------------+---------+-------+
| Workload | Query | File Format | Avg(s) | Base Avg(s) | Delta(Avg) | StdDev(%) | Base StdDev(%) | Iters | Median Diff(%) | MW Zval | Tval |
+----------+----------+-----------------------+--------+-------------+------------+-----------+----------------+-------+----------------+---------+-------+
| TPCH(2) | TPCH-Q18 | parquet / none / none | 1.22 | 1.19 | +1.93% | 3.81% | 4.46% | 20 | +3.34% | 1.62 | 1.46 |
| TPCH(2) | TPCH-Q10 | parquet / none / none | 0.74 | 0.73 | +1.97% | 3.36% | 2.94% | 20 | +0.97% | 1.88 | 1.95 |
| TPCH(2) | TPCH-Q11 | parquet / none / none | 0.49 | 0.48 | +1.91% | 6.19% | 4.64% | 20 | +0.25% | 0.95 | 1.09 |
| TPCH(2) | TPCH-Q4 | parquet / none / none | 0.43 | 0.43 | +1.99% | 6.26% | 5.86% | 20 | +0.15% | 0.92 | 1.03 |
| TPCH(2) | TPCH-Q15 | parquet / none / none | 0.50 | 0.49 | +1.82% | 7.32% | 6.35% | 20 | +0.26% | 1.01 | 0.83 |
| TPCH(2) | TPCH-Q1 | parquet / none / none | 0.98 | 0.97 | +0.79% | 4.64% | 2.73% | 20 | +0.36% | 0.77 | 0.65 |
| TPCH(2) | TPCH-Q19 | parquet / none / none | 0.83 | 0.83 | +0.65% | 3.33% | 2.80% | 20 | +0.44% | 2.18 | 0.67 |
| TPCH(2) | TPCH-Q14 | parquet / none / none | 0.62 | 0.62 | +0.97% | 2.86% | 1.00% | 20 | +0.04% | 0.13 | 1.42 |
| TPCH(2) | TPCH-Q3 | parquet / none / none | 0.88 | 0.87 | +0.57% | 2.17% | 1.74% | 20 | +0.29% | 1.15 | 0.92 |
| TPCH(2) | TPCH-Q12 | parquet / none / none | 0.53 | 0.53 | +0.27% | 4.58% | 5.78% | 20 | +0.46% | 1.47 | 0.16 |
| TPCH(2) | TPCH-Q17 | parquet / none / none | 0.72 | 0.72 | +0.15% | 3.64% | 5.55% | 20 | +0.21% | 0.86 | 0.10 |
| TPCH(2) | TPCH-Q21 | parquet / none / none | 2.05 | 2.05 | +0.21% | 1.99% | 2.37% | 20 | +0.01% | 0.25 | 0.30 |
| TPCH(2) | TPCH-Q5 | parquet / none / none | 1.28 | 1.27 | +0.24% | 1.61% | 1.80% | 20 | -0.02% | -0.57 | 0.44 |
| TPCH(2) | TPCH-Q13 | parquet / none / none | 1.27 | 1.27 | -0.34% | 1.69% | 1.83% | 20 | -0.20% | -1.65 | -0.61 |
| TPCH(2) | TPCH-Q7 | parquet / none / none | 1.72 | 1.73 | -0.55% | 2.40% | 1.69% | 20 | -0.03% | -0.42 | -0.83 |
| TPCH(2) | TPCH-Q8 | parquet / none / none | 1.27 | 1.28 | -0.68% | 3.10% | 3.89% | 20 | -0.06% | -0.54 | -0.62 |
| TPCH(2) | TPCH-Q6 | parquet / none / none | 0.36 | 0.36 | -0.84% | 0.79% | 3.51% | 20 | -0.07% | -0.36 | -1.04 |
| TPCH(2) | TPCH-Q2 | parquet / none / none | 0.65 | 0.65 | -1.17% | 4.76% | 5.99% | 20 | -0.05% | -0.25 | -0.69 |
| TPCH(2) | TPCH-Q9 | parquet / none / none | 1.59 | 1.62 | -2.01% | 1.45% | 5.12% | 20 | -0.16% | -1.24 | -1.69 |
| TPCH(2) | TPCH-Q20 | parquet / none / none | 0.68 | 0.69 | -1.73% | 4.35% | 4.43% | 20 | -0.49% | -1.74 | -1.25 |
| TPCH(2) | TPCH-Q22 | parquet / none / none | 0.38 | 0.40 | -2.89% | 7.42% | 6.39% | 20 | -0.21% | -0.66 | -1.34 |
| TPCH(2) | TPCH-Q16 | parquet / none / none | 0.59 | 0.62 | -4.01% | 6.33% | 5.83% | 20 | -4.72% | -1.39 | -2.13 |
+----------+----------+-----------------------+--------+-------------+------------+-----------+----------------+-------+----------------+---------+-------+
Change-Id: I839d7a3a2f5e1309c33a1f66013ef11628c5dc11
Reviewed-on: http://gerrit.cloudera.org:8080/12797
Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
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51ff47d05e |
IMPALA-5168: Codegen HASH_PARTITIONED KrpcDataStreamSender::Send()
This change codegens the hash partitioning logic of KrpcDataStreamSender::Send() when the partitioning strategy is HASH_PARTITIONED. It does so by unrolling the loop which evaluates each row against the partitioning expressions and hashes the result. It also replaces the number of channels of that sender with a constant at runtime. With this change, we get reasonable speedup with some benchmarks: +------------+-----------------------+---------+------------+------------+----------------+ | Workload | File Format | Avg (s) | Delta(Avg) | GeoMean(s) | Delta(GeoMean) | +------------+-----------------------+---------+------------+------------+----------------+ | TPCH(_300) | parquet / none / none | 20.03 | -6.44% | 13.56 | -7.15% | +------------+-----------------------+---------+------------+------------+----------------+ +---------------------+-----------------------+---------+------------+------------+----------------+ | Workload | File Format | Avg (s) | Delta(Avg) | GeoMean(s) | Delta(GeoMean) | +---------------------+-----------------------+---------+------------+------------+----------------+ | TARGETED-PERF(_300) | parquet / none / none | 58.59 | -5.56% | 12.28 | -5.30% | +---------------------+-----------------------+---------+------------+------------+----------------+ +-------------------------+-----------------------+---------+------------+------------+----------------+ | Workload | File Format | Avg (s) | Delta(Avg) | GeoMean(s) | Delta(GeoMean) | +-------------------------+-----------------------+---------+------------+------------+----------------+ | TPCDS-UNMODIFIED(_1000) | parquet / none / none | 15.60 | -3.10% | 7.16 | -4.33% | +-------------------------+-----------------------+---------+------------+------------+----------------+ +-------------------+-----------------------+---------+------------+------------+----------------+ | Workload | File Format | Avg (s) | Delta(Avg) | GeoMean(s) | Delta(GeoMean) | +-------------------+-----------------------+---------+------------+------------+----------------+ | TPCH_NESTED(_300) | parquet / none / none | 30.93 | -3.02% | 17.46 | -4.71% | +-------------------+-----------------------+---------+------------+------------+----------------+ Change-Id: I1c44cc9312c062cc7a5a4ac9156ceaa31fb887ff Reviewed-on: http://gerrit.cloudera.org:8080/10421 Reviewed-by: Michael Ho <kwho@cloudera.com> Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com> |