test_data_cache.py was added as part of IMPALA-8341 to verify
that the DataCache hit / miss counts and the DataCache metrics
are working as expected. The test seems to fail intermittently
due to unexpected cache misses.
Part of the test creates a temp table from tpch_parquet.lineitem
and uses it to join against tpch_parquet.lineitem itself on the
l_orderkey column. The test expects a complete cache hit for
tpch_parquet.lineitem when joining against the temp table as it
should be cached entirely as part of CTAS statement. However, this
doesn't work as expected all the time. In particular, the data cache
internally divides up the key space into multiple shards and a key
is hashed to determine the shard it belongs to. By default, the
number of shards is the same as number of CPU cores (e.g. 16 for AWS
m5-4xlarge instance). Since the cache size is set to 500MB, each shard
will have a capacity of 31MB only. In some cases, it's possible that
some rows of l_orderkey are evicted if the shard they belong to grow
beyond 31MB. The problem is not deterministic as part of the cache key
is the modification time of the file, which changes from run-to-run as
it's essentially determined by the data loading time of the job. This
leads to flakiness of the test.
To fix this problem, this patch forces the data cache to use a single
shard only for determinisim. In addition, the test is also skipped for
non-HDFS and HDFS erasure encoding builds as it's dependent on the scan
range assignment. To exercise the cache more extensively, the plan is
to enable it by default for S3 builds instead of relying on BE and E2E
tests only.
Testing done:
- Ran test_data_cache.py 10+ times, each with different mtime
for tpch_parquet.lineitem; Used to fail 2 out of 3 runs.
Change-Id: I98d5b8fa1d3fb25682a64bffaf56d751a140e4c9
Reviewed-on: http://gerrit.cloudera.org:8080/13242
Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
This is a patch based on PhilZ's prototype: https://gerrit.cloudera.org/#/c/12683/
This change implements an IO data cache which is backed by
local storage. It implicitly relies on the OS page cache
management to shuffle data between memory and the storage
device. This is useful for caching data read from remote
filesystems (e.g. remote HDFS data node, S3, ABFS, ADLS).
A data cache is divided into one or more partitions based on
the configuration string which is a list of directories, separated
by comma, followed by the storage capacity per directory.
An example configuration string is like the following:
--data_cache_config=/data/0,/data/1:150GB
In the configuration above, the cache may use up to 300GB of
storage space, with 150GB max for /data/0 and /data/1 respectively.
Each partition has a meta-data cache which tracks the mappings
of cache keys to the locations of the cached data. A cache key
is a tuple of (file's name, file's modification time, file offset)
and a cache entry is a tuple of (backing file, offset in the backing
file, length of the cached data, optional checksum). Note that the
cache currently doesn't support overlapping ranges. In other words,
if the cache contains an entry of a file for range [m, m+4MB), a lookup
for [m+4K, m+8K) will miss in the cache. In practice, we haven't seen
this as a problem but this may require further evaluation in the future.
Each partition stores its set of cached data in backing files created
on local storage. When inserting new data into the cache, the data is
appended to the current backing file in use. The storage consumption
of each cache entry counts towards the quota of that partition. When a
partition reaches its capacity, the least recently used (LRU) data in
that partition is evicted. Evicted data is removed from the underlying
storage by punching holes in the backing file it's stored in. As a
backing file reaches a certain size (by default 4TB), new data will
stop being appended to it and a new file will be created instead. Note
that due to hole punching, the backing file is actually sparse. When
the number of backing files per partition exceeds,
--data_cache_max_files_per_partition, files are deleted in the order
in which they are created. Stale cache entries referencing deleted
files are erased lazily or evicted due to inactivity.
Optionally, checksumming can be enabled to verify read from the cache
is consistent with what was inserted and to verify that multiple attempted
insertions with the same cache key have the same cache content.
Checksumming is enabled by default for debug builds.
To probe for cached data in the cache, the interface Lookup() is used;
To insert data into the cache, the interface Store() is used. Please note
that eviction happens inline currently during Store().
This patch also added two startup flags for start-impala-cluster.py:
'--data_cache_dir' specifies the base directory in which each Impalad
creates the caching directory
'--data_cache_size' specifies the capacity string for each cache directory.
Testing done:
- added a new BE and EE test
- exhaustive (debug, release) builds with cache enabled
- core ASAN build with cache enabled
Perf:
- 16-streams TPCDS at 3TB in a 20 node S3 cluster shows about 30% improvement
over runs without the cache. Each node has a cache size of 150GB per node.
The performance is at parity with a configuration of a HDFS cluster using
EBS as the storage.
Change-Id: I734803c1c1787c858dc3ffa0a2c0e33e77b12edc
Reviewed-on: http://gerrit.cloudera.org:8080/12987
Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
