Previously Impala disallowed LOAD DATA and INSERT on S3. This patch
functionally enables LOAD DATA and INSERT on S3 without making major
changes for the sake of improving performance over S3. This patch also
enables both INSERT and LOAD DATA between file systems.
S3 does not support the rename operation, so the staged files in S3
are copied instead of renamed, which contributes to the slow
performance on S3.
The FinalizeSuccessfulInsert() function now does not make any
underlying assumptions of the filesystem it is on and works across
all supported filesystems. This is done by adding a full URI field to
the base directory for a partition in the TInsertPartitionStatus.
Also, the HdfsOp class now does not assume a single filesystem and
gets connections to the filesystems based on the URI of the file it
is operating on.
Added a python S3 client called 'boto3' to access S3 from the python
tests. A new class called S3Client is introduced which creates
wrappers around the boto3 functions and have the same function
signatures as PyWebHdfsClient by deriving from a base abstract class
BaseFileSystem so that they can be interchangeably through a
'generic_client'. test_load.py is refactored to use this generic
client. The ImpalaTestSuite setup creates a client according to the
TARGET_FILESYSTEM environment variable and assigns it to the
'generic_client'.
P.S: Currently, the test_load.py runs 4x slower on S3 than on
HDFS. Performance needs to be improved in future patches. INSERT
performance is slower than on HDFS too. This is mainly because of an
extra copy that happens between staging and the final location of a
file. However, larger INSERTs come closer to HDFS permformance than
smaller inserts.
ACLs are not taken care of for S3 in this patch. It is something
that still needs to be discussed before implementing.
Change-Id: I94e15ad67752dce21c9b7c1dced6e114905a942d
Reviewed-on: http://gerrit.cloudera.org:8080/2574
Reviewed-by: Sailesh Mukil <sailesh@cloudera.com>
Tested-by: Internal Jenkins
Some TimestampValue converting functions assume caller
ensures TimestampValue instance has a valid date or time
but that's not true. Change those functions to return
result in output parameter and return boolean to indicate
the conversion is good or not.
Change-Id: I7a68a1e14d9c4ee5d83da760d4d76c20c36bc359
(cherry picked from commit 47d8977f5976b9be405f44add966820138fbda6f)
Reviewed-on: http://gerrit.cloudera.org:8080/2195
Reviewed-by: Juan Yu <jyu@cloudera.com>
Tested-by: Internal Jenkins
Aggregations are implemented as a distributed pre-aggregation, an
exchange, then a final aggregation that produces the results of the
aggregation. In many cases the pre-aggregation significantly reduces the
amount of data to be exchanged. However, in other cases, the
preaggregation does not greatly reduce the amount of data exchanged or
can use a lot of memory and starve other operators that would benefit
more from the additional memory.
In these cases we would be better off "passing through" some input tuples
by transforming them into intermediate tuples without aggregating them.
This patch adds a streaming pre-aggregation mode to
PartitionedAggregationNode that tries to aggregate input rows with a
hash table, but can switch to passing through the input tuples (after
transforming them into the appropriate tuple format). It does this if
it hits a memory limit or if the aggregation is not sufficiently
reducing the node's output (specifically, if the number of aggregated
rows in the hash table is more than half the number of unaggregated rows
consumed by the pre-aggregation). Pre-aggregations never need to spill
because they can pass through rows when under memory pressure.
This initial implementation is quite conservative: it retains the
partitioning of the previous implementation because switching to a
single partition proved to regress performance of some queries while
improving others. It also always keeps hash tables around and updates
them with matching input rows so that reduction statistics are updated
and early decisions to pass through data can be reversed. Future work
could explore different approaches within the new framework to get
larger performance gains. Currently we see significant performance
benefits for queries with a very low reduction factor, e.g. group by on
a nearly unique column
Includes codegen support for the passthrough streaming.
Adds a query option, disable_streaming_preaggregations, in case a user
wants to revert to the old behaviour.
Adds TPC-H tests to exercise the new passthrough code path and updates
planner tests to include the new [STREAMING] detail added by the planner.
Change-Id: Ia40525340cba89a8c4e70164ae11447e96494664
Reviewed-on: http://gerrit.cloudera.org:8080/1698
Tested-by: Internal Jenkins
Reviewed-by: Dan Hecht <dhecht@cloudera.com>
PAGG and PHJ were using an all-or-nothing approach wrt spilling. In
particular, they were trying to switch to IO-sized buffers for both
streams (aggregated and unaggregated in PAGG; build and probe in PHJ)
of every partition (currently 16 partitions for a total of 32
streams), even if some of the streams had very few rows, they were
empty or simply they would not spill so there was no need to allocate
IO-buffers for them. That was increasing the min mem needed by those
operators in many queries.
This patch decouples the decision to switch to IO-buffers for each
stream of each partition. Streams will switch to IO-sized buffers
whenever the rows they contain do not fit in the first two small
buffers (64KB and 512KB respectively). When we decide to spill a
partition, we switch to IO buffers both streams.
With these change many streams of PAGG and PHJ nodes do not need to
use IO-sized buffers, reducing the min mem requirement. For example,
below is the min mem needed (in MBs) for some of the TPC-H queries.
Some need half or less mem from the mem they needed before:
TPC-H Q3: 645 -> 240
TPC-H Q5: 375 -> 245
TPC-H Q7: 685 -> 265
TPC-H Q8: 740 -> 250
TPC-H Q9: 650 -> 400
TPC-H Q18: 1100 -> 425
TPC-H Q20: 420 -> 250
TPC-H Q21: 975 -> 620
To make this small buffer optimization to work, we had to fix
IMPALA-2352. That is, the AllocateRow() call of
PAGG::ConstructIntermediateTuple() could return unsuccessfully just
because the small buffers of the stream were exhausted. In that case,
previously we would treat it as an indication that there is no memory
left, start spilling a partition and switching all stream to
IO-buffes. Now we make a best effort, trying to first
SwitchToIoffers() and if that is successful, we re-attempt the
AllocateRow() call. See IMPALA-2352 for more details.
Another change is that now SwitchToIoBuffers() will reset the flag
using_small_buffers_ back to false, in case we are in a very low
memory situation and it fails to get a buffer. That allows us to
retry calling SwitchToIoBuffers() once we free up some space. See
IMPALA-2330 for more details.
With the above fixes we should also have fixed IMPALA-2241 and
IMPALA-2271 that are essentially stream::using_small_buffers_-related
DCHECKs.
This patch adds all 22 TPC-H queries in test_mem_usage_scaling test
and updates the per-query min mem limits in it. Additionally, it adds
a new aggregation test that uses the TPC-H dataset for larger
aggregations (TestTPCHAggregationQueries). It also removes some
dead test code.
Change-Id: Ia8ccd0b76f6d37562be21fd4539aedbc2a864d38
Reviewed-on: http://gerrit.cloudera.org:8080/818
Reviewed-by: Ippokratis Pandis <ipandis@cloudera.com>
Tested-by: Internal Jenkins
Conflicts:
tests/query_test/test_aggregation.py
Many python files had a hashbang and the executable bit set though
they were not intended to be run a standalone script. That makes
determining which python files are actually scripts very difficult.
A future patch will update the hashbang in real python scripts so they
use $IMPALA_HOME/bin/impala-python.
Change-Id: I04eafdc73201feefe65b85817a00474e182ec2ba
Reviewed-on: http://gerrit.cloudera.org:8080/599
Reviewed-by: Casey Ching <casey@cloudera.com>
Reviewed-by: Taras Bobrovytsky <tbobrovytsky@cloudera.com>
Tested-by: Internal Jenkins
This patch encapsulates pytests's skipif markers in classes. It leads to the following
benefits:
- Provide context and grouping for tests being skipped.
- As we improve test reporting, annotations will give us a better idea of coverage.
Change-Id: Ib0557fb78c873047c214bb62bb6b045ceabaf0c9
Reviewed-on: http://gerrit.cloudera.org:8080/297
Reviewed-by: Ishaan Joshi <ishaan@cloudera.com>
Tested-by: Internal Jenkins
Reviewed-on: http://gerrit.cloudera.org:8080/343
Add skip markers for S3 that can be used to categorize the tests that
are skipped against S3 to help see what coverage is missing. Soon
we'll be reworking some tests and/or adding new tests to get back the
important gaps.
Also, add a mechanism to parameterize paths in the .test files, and
start using these new variables. This is a step toward enabling some
more tests against S3.
Finally, a fix for buildall.sh to stop the minicluster before applying
the metastore snapshot. Otherwise, this fails since the ms db is in
use.
Change-Id: I142434ed67bed407e61d7b2c90f825734fc0dce0
Reviewed-on: http://gerrit.cloudera.org:8080/127
Reviewed-by: Dan Hecht <dhecht@cloudera.com>
Tested-by: Internal Jenkins
This patch introduces a new pytest marker that skip tests that currently don't work when
s3 is used as the underlying file system. The set of blacklisted tests is a superset of
tests that cannot be run with s3. Follow up patches will remove some of the test files
from the blacklist.
Change-Id: I39a58223d3435f0bd6496ffd00a2d483b751693d
Reviewed-on: http://gerrit.cloudera.org:8080/82
Reviewed-by: Ishaan Joshi <ishaan@cloudera.com>
Tested-by: Internal Jenkins
The distinct tests exercise the aggregation node codepaths. This patch moves the
distinct tests to test_aggregation, so that running this test will cover most of the
aggregation code.
Change-Id: Icbe04c51a91e3fda057439a83fca3e61a3890e71
Reviewed-on: http://gerrit.sjc.cloudera.com:8080/5868
Reviewed-by: Ishaan Joshi <ishaan@cloudera.com>
Tested-by: jenkins
This patch does a few things:
1) Move the metadata tests into their own folder under tests/. I think it's useful to
loosely categorize them so it's easier to run a subset of the tests that are most
useful for the changes you are making.
2) Reduce the test vectors for query_tests. We should have identical coverage in
the daily exhaustive runs but the normal runs should be much better. In particular,
deemphasizing scanner tests since that code is more stable now.
3) Misc test cleanup/consolidate python test files/etc.
Change-Id: I03c2f34877aed192c2a50665bd5e15fa85e12f1e
Reviewed-on: http://gerrit.sjc.cloudera.com:8080/3831
Tested-by: jenkins
Reviewed-by: Nong Li <nong@cloudera.com>
The following changes are included in this commit:
1. Modified the alltypesagg table to include an additional partition key
that has nulls.
2. Added a number of tests in hdfs.test that exercise the partition
pruning logic (see IMPALA-887).
3. Modified all the tests that are affected by the change in alltypesagg.
Change-Id: I1a769375aaa71273341522eb94490ba5e4c6f00d
Reviewed-on: http://gerrit.ent.cloudera.com:8080/2874
Reviewed-by: Dimitris Tsirogiannis <dtsirogiannis@cloudera.com>
Tested-by: jenkins
Reviewed-on: http://gerrit.ent.cloudera.com:8080/3236
I looked at the latest run from master and took the tests suites that had long
execution times. This cleans those test suites up to either completely disable them
on 'core' or add constraints to limit the number of test vectors. It shouldn't impact
nightly coverage since we still run the same tests exhaustively.
Change-Id: I10c78c35155b00de0c36d9fc0923b2b1fc6b44de
Reviewed-on: http://gerrit.ent.cloudera.com:8080/3119
Reviewed-by: Marcel Kornacker <marcel@cloudera.com>
Tested-by: jenkins
Reviewed-on: http://gerrit.ent.cloudera.com:8080/3125
Reviewed-by: Lenni Kuff <lskuff@cloudera.com>
This patch allows the text scanner to read 'inf' or 'Infinity' from a
row and correctly translate it into floating-point infinity. It also
adds is_inf() and is_nan() builtins.
Finally, we change the text table writer to write Infinity and NaN for
compatibility with Hive.
In the future, we might consider adding nan / inf literals to our
grammar (postgres has this, see:
http://www.postgresql.org/docs/9.3/static/datatype-numeric.html).
Change-Id: I796f2852b3c6c3b72e9aae9dd5ad228d188a6ea3
Reviewed-on: http://gerrit.ent.cloudera.com:8080/2393
Reviewed-by: Henry Robinson <henry@cloudera.com>
Tested-by: jenkins
(cherry picked from commit 58091355142cadd2b74874d9aa7c8ab6bf3efe2f)
Reviewed-on: http://gerrit.ent.cloudera.com:8080/2483
Some tests have constraints that were there only to help reduce runtime which
reduces coverage when running in exhaustive mode. The majority of the constraints
are because it adds no value to run the test across additional dimensions (or
it is invalid to run with those dimensions). Updates the tests that have
legitimate constraints to use two new helper methods for constraining the table format
dimension:
create_uncompressed_text_dimension()
create_parquet_dimension()
These will create a dimension that will produce a single test vector, either
uncompressed text or parquet respectively.
Change-Id: Id85387c1efd5d192f8059ef89934933389bfe247
Reviewed-on: http://gerrit.ent.cloudera.com:8080/2149
Reviewed-by: Lenni Kuff <lskuff@cloudera.com>
Tested-by: jenkins
(cherry picked from commit e02acbd469bc48c684b2089405b4a20552802481)
Reviewed-on: http://gerrit.ent.cloudera.com:8080/2290
With this change the Python tests will now be called as part of buildall and
the corresponding Java tests have been disabled. The new tests can also be
invoked calling ./tests/run-tests.sh directly.
This includes a fix from Nong that caused wrong results for limit on non-io
manager formats.
This is the first set of changes required to start getting our functional test
infrastructure moved from JUnit to Python. After investigating a number of
option, I decided to go with a python test executor named py.test
(http://pytest.org/). It is very flexible, open source (MIT licensed), and will
enable us to do some cool things like parallel test execution.
As part of this change, we now use our "test vectors" for query test execution.
This will be very nice because it means if load the "core" dataset you know you
will be able to run the "core" query tests (specified by --exploration_strategy
when running the tests).
You will see that now each combination of table format + query exec options is
treated like an individual test case. this will make it much easier to debug
exactly where something failed.
These new tests can be run using the script at tests/run-tests.sh
