Currently the only way to refresh metadata for a partition was to refresh
the whole table. This is a relatively time consuming process especially if
there are many partitions and only one is to be refreshed.
This patch allows the client to REFRESH on a single partition by using the
following syntax:
REFRESH [database_name.]table_name PARTITION (partition_spec)
Testing:
Added parsing and authorization tests in ParserTest.java and
AuthorizationTest.java respectively. A new test file
"test_refresh_partition.py" was added for testing functionality.
Performance:
For a table with 10000 partitions and 1 file per partition
execResetMetadata() Total Execution Time
Refresh Table 3795 ms 4630 ms
Refersh Partition 42 ms 680 ms
We see that the time to refresh improves by a factor of 90x but due to
significant overhead of about 640ms in this case the effective improvement
is about 7x. As the size of the table and number of partitions increase,
this improvement would be more significant.
Change-Id: Ia9aa25d190ada367fbebaca47ae8b2cafbea16fb
Reviewed-on: http://gerrit.cloudera.org:8080/3813
Reviewed-by: Dimitris Tsirogiannis <dtsirogiannis@cloudera.com>
Tested-by: Internal Jenkins
With this commit we enable loading of TPC-H data in Kudu tables and
running the 22 TPC-H queries against Kudu. Since Kudu doesn't support
the decimal data type, we had to modify the queries by using round()
function and update the test results.
Change-Id: I3a5de71fefa92a78970226d8f49ef445d28f9289
Reviewed-on: http://gerrit.cloudera.org:8080/3789
Reviewed-by: Dimitris Tsirogiannis <dtsirogiannis@cloudera.com>
Tested-by: Internal Jenkins
Compressed text formats currently require entire compressed
files be read into memory to be decompressed in a single call
to the decompression codec. This changes the HdfsTextScanner
to drive gzip in a streaming mode, i.e. produce partial output
as input is consumed.
Change-Id: Id5c0805e18cf6b606bcf27a5df4b5f58895809fd
Reviewed-on: http://gerrit.sjc.cloudera.com:8080/5233
Reviewed-by: Matthew Jacobs <mj@cloudera.com>
Tested-by: jenkins
(cherry picked from commit 05c3cc55e7a601d97adc4eebe03f878c68a33e56)
Reviewed-on: http://gerrit.sjc.cloudera.com:8080/5385
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
