verify that the exception message contains the correct error;
verify that excpected exception is thrown;
verify that no exception is thrown when abort_on_error is set to false
- executor takes report callback; passed in by ImpalaServer::FragmentExecState
- the PlanFragmentExecutor invokes profile reporting cb in background thread.
- RuntimeProfile is now thread-safe and has an RuntimeProfile::Update()
Also included:
- a number of bug fixes related to async cancellation of query
and propagation of errors through PlanFragmentExecutor/Coordinator/ImpalaServer.
- changing COUNTER_SCOPED_TIMER to SCOPED_TIMER
- derived counters: RuntimeProfile now lets you add counters that return a
value via a function call, which is useful for reporting something like normalized
ScanNode throughput; retrofitted to ScanNode and all subclasses
- changed coordinator to make cancellation atomic wrt recognition of an error status
for the overall query.
- Removed InProcessQueryExecutor from data-stream-test.
Added aggregate throughput counters to coordinator:
- all throughput counters are grouped in a sub-profile "AggregateThroughput"
- each scan node gets its own counter
- the value is aggregated across all registered backends which contain that node in
their plan fragments
I am temporarily disabling the TPC-H planner tests that require data to be
pre-loaded in temp tables. This resolves a problem where the TPC-H query tests
need to be run before the TPC-H planner tests. I have filed "IMP-171" to track
the work to re-enable these tests.
"distinctpc" and "distinctpcsa".
We've gathered statistics on an internal dataset (all columns) which is
part of our regression data. It's roughly 400mb, ~100 columns,
int/bigint/string type.
On Hive, it took roughly 64sec.
On this Impala implementation, it took 35sec. By adding inline to hash-util.h (which we don't),
we can achieve 24~26sec.
Change-Id: Ibcba3c9512b49e8b9eb0c2fec59dfd27f14f84c3
Fixed a problem where we were not properly looking up the dataset associated
with the given workload if it had non-word characters in its name (a-z & _). Also cut down
on the execution time of the hive-benchmark workload under the "core" vector.
This change updates the run-benchmark script to enable it to target one or more
workloads. Now benchmarks can be run like:
./run-benchmark --workloads=hive-benchmark,tpch
We lookup the workload in the workloads directory, then read the associated
query .test files and start executing them.
To ensure the queries are not duplicated between benchmark and query tests, I
moved all existing queries (under fe/src/test/resources/* to the workloads
directory. You do NOT need to look through all the .test files, I've just moved
them. The one new file is the 'hive-benchmark.test' which contains the hive
benchmark queries.
Also added support for generating schema for different scale factors as well as
executing against these scale factors. For example, let's say we have a dataset
with a scale factor called "SF1". We would first generate the schema using:
./generate_schema_statements --workload=<workload> --scale_factor="SF3"
This will create tables with a unique names from the other scale factors.
Run the generated .sql file to load the data. Alternatively, the data can loaded
by running a new python script:
./bin/load-data.py -w <workload1>,<workload2> -e <exploration strategy> -s [scale factor]
For example: load-data.sh -w tpch -e core -s SF3
Then run against this:
./run-benchmark --workloads=<workload> --scale_factor=SF3
This changeset also includes a few other minor tweaks to some of the test
scripts.
Change-Id: Ife8a8d91567d75c9612be37bec96c1e7780f50d6
This change moves (almost) all the functional data loading to the new data
loading framework. This removes the need for the create.sql, load.sql, and
load-raw-data.sql file. Instead we just have the single schema template file:
testdata/datasets/functional/functional_schema_template.sql
This template can be used to generate the schema for all file formats and
compression variations. It also should help make loading data easier. Now you
can run:
bin/load-impala-data.sh "query-test" "exhaustive"
And get all data needed for running the query tests.
This change also includes the initial changes for new dataset/workload directory
structure. The new structure looks like:
testdata/workload <- Will contain query files and test vectors/dimensions
testdata/datasets <- WIll contain the data files and schema templates
Note: This is the first part of the change to this directory structure - it's
not yet complete. # Please enter the commit message for your changes. Lines starting
