This commit adds support for Kudu-specific column options in CREATE
TABLE statements. The syntax is:
CREATE TABLE tbl_name ([col_name type [PRIMARY KEY] [option [...]]] [, ....])
where option is:
| NULL
| NOT NULL
| ENCODING encoding_val
| COMPRESSION compression_algorithm
| DEFAULT expr
| BLOCK_SIZE num
The output of the SHOW CREATE TABLE statement was altered to include all the specified
column options for Kudu tables.
Change-Id: I727b9ae1b7b2387db752b58081398dd3f3449c02
Reviewed-on: http://gerrit.cloudera.org:8080/5026
Reviewed-by: Dimitris Tsirogiannis <dtsirogiannis@cloudera.com>
Tested-by: Internal Jenkins
Before this patch an unclear error message was returned if DATE or
DATETIME appeared in the select list after a star expansion. This was
because DATE and DATETIME PrimitiveType was serialized as INVALID_TYPE.
This is fixed by serializing correctly.
Change-Id: I9019b4bfd219f94e554c795befd3ff5e39706ea9
Reviewed-on: http://gerrit.cloudera.org:8080/4859
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins
This commit adds support for non-covering range partitions in Kudu
tables. The SPLIT ROWS clause is now deprecated and no longer supported.
The following new syntax provides more flexibility in creating range
partitions and it supports bounded and unbounded ranges as well as single value
partitions; multi-column range partitions are supported as well.
The new syntax is:
DISTRIBUTE BY RANGE (col_list)
(
PARTITION lower_1 <[=] VALUES <[=] upper_1,
PARTITION lower_2 <[=] VALUES <[=] upper_2,
....
PARTITION lower_n <[=] VALUES <[=] upper_n,
PARTITION VALUE = val_1,
....
PARTITION VALUE = val_n
)
Multi-column range partitions are specified as follows:
DISTRIBUTE BY RANGE (col1, col2,..., coln)
(
PARTITION VALUE = (col1_val, col2_val, ..., coln_val),
....
PARTITION VALUE = (col1_val, col2_val, ..., coln_val)
)
Change-Id: I6799c01a37003f0f4c068d911a13e3f060110a06
Reviewed-on: http://gerrit.cloudera.org:8080/4856
Reviewed-by: Dimitris Tsirogiannis <dtsirogiannis@cloudera.com>
Tested-by: Internal Jenkins
This patch prevents an invalid decimal type in an Avro file schema from
crashing Impala. Most invalid Avro schemas are caught by the frontend,
but file schemas still need to be validated by the backend.
After this patch files with bad schemas are skipped.
Testing:
This was hit very rarely by the scanner fuzzing. Added a regression test that
scans a file with a bad schema.
Change-Id: I25a326ee2220bc14d3b5f887dc288b4adf859cfc
Reviewed-on: http://gerrit.cloudera.org:8080/4876
Reviewed-by: Tim Armstrong <tarmstrong@cloudera.com>
Tested-by: Internal Jenkins
This commit modifies the stress test framework to run TPC-H and TPC-DS
workloads against Kudu. The follwing changes are included in this
commit:
1. Created template files with DDL and DML statements for loading TPC-H and
TPC-DS data in Kudu
2. Created a script (load-tpc-kudu.py) to load data in Kudu. The
script is invoked by the stress test runner to load test data in an
existing Impala/Kudu cluster (both local and CM-managed clusters are
supported).
3. Created SQL files with TPC-DS queries to be executed in Kudu. SQL
files with TPC-H queries for Kudu were added in a previous patch.
4. Modified the stress test runner to take additional parameters
specific to Kudu (e.g. kudu master addr)
The stress test runner for Kudu was tested on EC2 clusters for both TPC-H
and TPC-DS workloads.
Missing functionality:
* No CRUD operations in the existing TPC-H/TPC-DS workloads for Kudu.
* Not all supported TPC-DS queries are included. Currently, only the
TPC-DS queries from the testdata/workloads/tpcds/queries directory
were modified to run against Kudu.
Change-Id: I3c9fc3dae24b761f031ee8e014bd611a49029d34
Reviewed-on: http://gerrit.cloudera.org:8080/4327
Reviewed-by: Dimitris Tsirogiannis <dtsirogiannis@cloudera.com>
Tested-by: Internal Jenkins
With this commit we simplify the syntax and handling of CREATE TABLE
statements for both managed and external Kudu tables.
Syntax example:
CREATE TABLE foo(a INT, b STRING, PRIMARY KEY (a, b))
DISTRIBUTE BY HASH (a) INTO 3 BUCKETS,
RANGE (b) SPLIT ROWS (('abc', 'def'))
STORED AS KUDU
Changes:
1) Remove the requirement to specify table properties such as key
columns in tblproperties.
2) Read table schema (column definitions, primary keys, and distribution
schemes) from Kudu instead of the HMS.
3) For external tables, the Kudu table is now required to exist at the
time of creation in Impala.
4) Disallow table properties that could conflict with an existing
table. Ex: key_columns cannot be specified.
5) Add KUDU as a file format.
6) Add a startup flag to impalad to specify the default Kudu master
addresses. The flag is used as the default value for the table
property kudu_master_addresses but it can still be overriden
using TBLPROPERTIES.
7) Fix a post merge issue (IMPALA-3178) where DROP DATABASE CASCADE
wasn't implemented for Kudu tables and silently ignored. The Kudu
tables wouldn't be removed in Kudu.
8) Remove DDL delegates. There was only one functional delegate (for
Kudu) the existence of the other delegate and the use of delegates in
general has led to confusion. The Kudu delegate only exists to provide
functionality missing from Hive.
9) Add PRIMARY KEY at the column and table level. This syntax is fairly
standard. When used at the column level, only one column can be
marked as a key. When used at the table level, multiple columns can
be used as a key. Only Kudu tables are allowed to use PRIMARY KEY.
The old "kudu.key_columns" table property is no longer accepted
though it is still used internally. "PRIMARY" is now a keyword.
The ident style declaration is used for "KEY" because it is also used
for nested map types.
10) For managed tables, infer a Kudu table name if none was given.
The table property "kudu.table_name" is optional for managed tables
and is required for external tables. If for a managed table a Kudu
table name is not provided, a table name will be generated based
on the HMS database and table name.
11) Use Kudu master as the source of truth for table metadata instead
of HMS when a table is loaded or refreshed. Table/column metadata
are cached in the catalog and are stored in HMS in order to be
able to use table and column statistics.
Change-Id: I7b9d51b2720ab57649abdb7d5c710ea04ff50dc1
Reviewed-on: http://gerrit.cloudera.org:8080/4414
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins
Adds initial support for the functional-query test workload
for Kudu tables.
There are a few issues that make loading the functional
schema difficult on Kudu:
1) Kudu tables must have one or more columns that together
constitute a unique primary key.
a) Primary key columns must currently be the first columns
in the table definition (KUDU-1271).
b) Primary key columns cannot be nullable (KUDU-1570).
2) Kudu tables must be specified with distribution
parameters.
(1) limits the tables that can be loaded without ugly
workarounds. This patch only includes important tables that
are used for relevant tests, most notably the alltypes*
family. In particular, alltypesagg is important but it does
not have a set of columns that are non-nullable and form a unique
primary key. As a result, that table is created in Kudu with
a different name and an additional BIGINT column for a PK
that is a unique index and is generated at data loading time
using the ROW_NUMBER analytic function. A view is then
wrapped around the underlying table that matches the
alltypesagg schema exactly. When KUDU-1570 is resolved, this
can be simplified.
(2) requires some additional considerations and custom
syntax. As a result, the DDL to create the tables is
explicitly specified in CREATE_KUDU sections in the
functional_schema_constraints.csv, and an additional
DEPENDENT_LOAD_KUDU section was added to specify custom data
loading DML that differs from the existing DEPENDENT_LOAD.
TODO: IMPALA-4005: generate_schema_statements.py needs refactoring
Tests that are not relevant or not yet supported have been
marked with xfail and a skip where appropriate.
TODO: Support remaining functional tables/tests when possible.
Change-Id: Iada88e078352e4462745d9a9a1b5111260d21acc
Reviewed-on: http://gerrit.cloudera.org:8080/4175
Reviewed-by: Matthew Jacobs <mj@cloudera.com>
Tested-by: Internal Jenkins
The bug: We used to register privilege requests for table refs in TableRef.analyze()
which only got called for unresolved TableRefs. As a result, a reference to a view that
contains a subquery did not get properly authorized, explained as follows.
1. In the first analysis pass the view is replaced by a an InlineViewRef and we
correctly register an authorizarion request.
2. We rewrite the subquery via the StmtRewriter and wipe the analysis state, but
preserve the InlineViewRef that replaces the view reference.
3. The rewritten statement is analyzed again, but since an InlineViewRef is
considered to be resolved, we never call TableRef.analyze(), and hence
never register an authorization event for the view.
The fix: We now register authorization and auditing events when calling analyze() on a
resolved TableRef (BaseTableRef, InlineViewRef, CollectionTableRef).
Change-Id: I18fa8af9a94ce190c5a3c29c3221c659a2ace659
Reviewed-on: http://gerrit.cloudera.org:8080/3783
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins
Added checks/error handling:
* Negative string lengths while decoding dictionary or data page.
* Buffer overruns while decoding dictionary or data page.
* Some metadata FILECHECKs were converted to statuses.
Testing:
Unit tests for:
* decoding of strings with negative lengths
* truncation of all parquet types
* dictionary creation correctly handling error returns from Decode().
End-to-end tests for handling of negative string lengths in
dictionary- and plain-encoded data in corrupt files, and for
handling of buffer overruns for string data. The corrupted
parquet files were generated by hacking Impala's parquet
writer to write invalid lengths, and by hacking it to
write plain-encoded data instead of dictionary-encoded
data by default.
Performance:
set num_nodes=1;
set num_scanner_threads=1;
select * from biglineitem where l_orderkey = -1;
I inspected MaterializeTupleTime. Before the average was 8.24s and after
was 8.36s (a 1.4% slowdown, within the standard deviation of 1.8%).
Change-Id: Id565a2ccb7b82f9f92cc3b07f05642a3a835bece
Reviewed-on: http://gerrit.cloudera.org:8080/3387
Reviewed-by: Tim Armstrong <tarmstrong@cloudera.com>
Tested-by: Internal Jenkins
This patch adds error checking to the Avro scanner (both the codegen'd
and interepted paths), including out-of-bounds checks and data
validity checks.
I ran a local benchmark using the following queries:
set num_scanner_threads=1;
select count(i) from default.avro_bigints_big; # file contains only longs
select max(l_orderkey) from biglineitem_avro; # file has tpch.lineitem schema
Both benchmark queries see negligable or no performance impact.
This patch adds a new Avro scanner unit test and an end-to-end test
that queries several corrupted files, as well as updates the zig-zag
varlen int unit test.
Change-Id: I801a11c496a128e02c564c2a9c44baa5a97be132
Reviewed-on: http://gerrit.cloudera.org:8080/3072
Reviewed-by: Dan Hecht <dhecht@cloudera.com>
Tested-by: Internal Jenkins
Adds a query option 'strict_mode' which treats integer and
floating pt overflows as parse errors. In the past,
overflows were ignored and the max value was returned. When
this query option is set, overflowing values are treated as if
they were completely invalid data, i.e. NULL is returned.
When abort_on_error is enabled, this means the query is
aborted.
Notes:
* DECIMAL overflow/underflow is already treated as an error.
* The handling in text-converter treats underflows the same
as overflows, so they would result in the same behavior.
However, floating point parsing never returns an underflow
today.
* We may also want to handle numeric values that are truncated
when parsing to integer types, e.g. 10.5 -> 10.
Change-Id: I7409c31ec0cb6fe0b2d9842b9f58fe1670914836
Reviewed-on: http://gerrit.cloudera.org:8080/3150
Reviewed-by: Matthew Jacobs <mj@cloudera.com>
Tested-by: Internal Jenkins
For IMPALA-1740 we added a test to insert.test, which creates a table and
inserts data. The table was created on HDFS by default and thus inserts with
compression enabled did not work. This change adds the required table to the
functional schema in the same way we do it for the other insert tests.
Change-Id: Ie68e7067b7a16218d27935820d5d1ce7035d2e6c
Reviewed-on: http://gerrit.cloudera.org:8080/2919
Reviewed-by: Tim Armstrong <tarmstrong@cloudera.com>
Tested-by: Internal Jenkins
HIVE-5795 introduced a parameter skip.header.line.count to skip header
lines from input files. This change introduces the capability to skip
an arbitrary number of header lines from csv input files on hdfs. The
size of the total file header must be smaller than
max_scan_range_length, otherwise an error will be reported. This is
necessary because scan ranges are not read in disk order, so there is
no way of identifying header lines except by counting from the start
of the first scan range.
[localhost:21000] > alter table t1 set
tblproperties('skip.header.line.count'='1');
Query: alter table t1 set tblproperties('skip.header.line.count'='1')
[localhost:21000] > select * from t1;
Query: select * from t1
+----+----+
| c1 | c2 |
+----+----+
| 1 | 1 |
| 2 | 2 |
| 3 | 3 |
+----+----+
Fetched 3 row(s) in 0.32s
[localhost:21000] > alter table t1 set
tblproperties('skip.header.line.count'='0');
Query: alter table t1 set tblproperties('skip.header.line.count'='0')
[localhost:21000] > select * from t1;
Query: select * from t1
+------+------+
| c1 | c2 |
+------+------+
| NULL | NULL |
| 1 | 1 |
| 2 | 2 |
| 3 | 3 |
+------+------+
WARNINGS: Error converting column: 0 TO INT (Data is: num1)
Error converting column: 1 TO DOUBLE (Data is: num2)
file: hdfs://localhost:20500/test-warehouse/t1/test.txt
record: num1,num2
Fetched 4 row(s) in 0.41s
Change-Id: I595f01a165d41499ca1956fe748ba3840a6eb543
Reviewed-on: http://gerrit.cloudera.org:8080/2110
Reviewed-by: Lars Volker <lv@cloudera.com>
Tested-by: Internal Jenkins
This field was included in the schema and data files, but the
checked-in generated parquet files didn't include it. It's not
referenced in any tests so we didn't catch it.
Change-Id: I5d394f074e7082fa12fafb7e57a144a83b3099a6
Reviewed-on: http://gerrit.cloudera.org:8080/2562
Reviewed-by: Tim Armstrong <tarmstrong@cloudera.com>
Tested-by: Internal Jenkins
These tests functionally test whether the following type of files
are able to be scanned properly:
1) Add a parquet file with multiple blocks such that each node has to
scan multiple blocks.
2) Add a parquet file with multiple blocks but only one row group
that spans the entire file. Only one scan range should do any work
in this case.
Change-Id: I4faccd9ce3fad42402652c8f17d4e7aa3d593368
Reviewed-on: http://gerrit.cloudera.org:8080/1500
Reviewed-by: Sailesh Mukil <sailesh@cloudera.com>
Tested-by: Internal Jenkins
This merges the 'feature/kudu' branch with cdh5-trunk as of commit:
055500cc753f87f6d1c70627321fcc825044e183
This patch is not a pure merge patch in the sense that goes beyond conflict
resolution to also address reviews to the 'feature/kudu' branch as a whole.
The review items and their resolution can be inspected at:
http://gerrit.cloudera.org:8080/#/c/1403/
Change-Id: I6dd4270cd17a4f5c02811c343726db3504275a92
Fix a bug in which Impala only reads the first stream
of a multi-stream bz2/gzip file.
Changes the bz2 decoder to read the file in a streaming
fashion rather than reading the entire file into memory
before it can be decompressed.
Change-Id: Icbe617d03a69953f0bf3aa0f7c30d34bc612f9f8
(cherry picked from commit b6d0b4e059329633dc50f1f73ebe35b7ac317a8e)
Reviewed-on: http://gerrit.cloudera.org:8080/2219
Reviewed-by: Juan Yu <jyu@cloudera.com>
Tested-by: Internal Jenkins
This patch also fixes the incorrect error message reported
in the JIRA.
Change-Id: I2c7b732767d154c36bc7189df5177d27a35d0d7b
Reviewed-on: http://gerrit.cloudera.org:8080/2267
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins
This patch is required for upgrading thirdparty.
After upgrading thirdparty, Hive OOMs in data loading TPCDS.
This patch fixes the OOM, but I have no idea why exactly it works.
I had tried several other approaches like increasing the
mapred and JVM heap memory to no avail.
Change-Id: I3c69e4c3bf0f24e0c3b6272c946f71c17e312e01
Reviewed-on: http://gerrit.cloudera.org:8080/2145
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins
The original purpose of the escapechartesttable was to test
Impala's behavior on text tables that have the same character
as line terminator and escape character. Recent changes in
Hive have made creating such a table impossible because
1) Only newline is allowed as the line terminator
2) Newline is forbidden as the escape character
See HIVE-11785 for details on the Hive changes.
This commit removes escapechartesttable and all associated
tests, but does not add the same enforcement rules as Hive.
These enforcement rules should be added in a follow-on change.
Change-Id: I2bd9755f4c2cc3d7dfd8d67c3759885951550f08
Reviewed-on: http://gerrit.cloudera.org:8080/1690
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Alex Behm <alex.behm@cloudera.com>
There was an incorrect DCHECK in the parquet scanner. If abort_on_error
is false, the intended behaviour is to skip to the next row group, but
the DCHECK assumed that execution should have aborted if a parse error
was encountered.
This also:
- Fixes a DCHECK after an empty row group. InitColumns() would try to
create empty scan ranges for the column readers.
- Uses metadata_range_->file() instead of stream_->filename() in the
scanner. InitColumns() was using stream_->filename() in error
messages, which used to work but now stream_ is set to NULL before
calling InitColumns().
Change-Id: I8e29e4c0c268c119e1583f16bd6cf7cd59591701
Reviewed-on: http://gerrit.cloudera.org:8080/1257
Reviewed-by: Dan Hecht <dhecht@cloudera.com>
Tested-by: Internal Jenkins
Loading functional data may fail if table_no_newline_part
partitions already exist. We should only ADD with IF NOT
EXISTS to handle this case as we do with other tables.
Change-Id: I5fe5c318d2cbbd5b5419394212b94a2fe7d386ce
Reviewed-on: http://gerrit.cloudera.org:8080/1261
Reviewed-by: Dan Hecht <dhecht@cloudera.com>
Tested-by: Internal Jenkins
The test_verify_runtime_profile test failed during C5.5 builds and
GVMs because this test relies on the table lineitem_multiblock to
have 3 blocks. However, due to the rules to load the data not being
followed in the functional_schema_template.sql file, the table ended
up being stored with only one block.
This change moves the data load to the end of create-load-data.sh
file which would load the data even for snapshots.
Change-Id: I78030dd390d2453230c4b7b581ae33004dbf71be
Reviewed-on: http://gerrit.cloudera.org:8080/1153
Reviewed-by: Sailesh Mukil <sailesh@cloudera.com>
Tested-by: Internal Jenkins
Impala supports reading Parquet files with multiple row groups but
with possible performance degradation due to remote reads. This patch
maximizes scan locality by allowing multiple impalads to scan the
rowgroups in their local splits. Each impalad starts a new scan range
for each split local to it if that split contains row group(s) that
need to be scanned.
Change-Id: Iaecc5fb8e89364780bc59dbfa9ae51d0d124d16e
Reviewed-on: http://gerrit.cloudera.org:8080/908
Reviewed-by: Sailesh Mukil <sailesh@cloudera.com>
Tested-by: Internal Jenkins
Hive does not allow DDL when an avro table has a timestamp column. This breaks data
loading. This change simply uses a string type to denote the previous timestamp column.
Change-Id: Id4eb42da3ac8a805d12b1c3ff35b200298269084
Reviewed-on: http://gerrit.cloudera.org:8080/745
Tested-by: Internal Jenkins
Reviewed-by: Ishaan Joshi <ishaan@cloudera.com>
Tested-by: Ishaan Joshi <ishaan@cloudera.com>
This patch modifies the Parquet scanner to resolve nested schemas, and
read and materialize collection types. The high-level modification is
to create a CollectionColumnReader that recursively materializes map-
and array-type slots.
This patch also adds many tests, most of which query a new table
called complextypestbl. This table contains hand-generated data that
is meant to expose edge cases in the scanner. The tests mostly test
the scanner, with a few tests of other functionality (e.g. array
serialization).
I ran a local benchmark comparing this scanner code to the original
scanner code on an expanded version of tpch_parquet.lineitem with
48009720 rows. My benchmark involved selecting different numbers of
columns with a single scanner thread, and I looked at the HDFS scan
node time in the query profiles. This code introduces a 10%-20%
regression in single-threaded scan time.
Change-Id: Id27fb728934e8346444f61752c9278d8010e5f3a
Reviewed-on: http://gerrit.cloudera.org:8080/576
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins
The limitation of the Avro JSON library not to handle \u0000 characters
is to avoid problems with builtin functions like strlen() that would
report wrong length when encountering such a character. Now, in the
case if Impala, for now, we don't support any Unicode characters.
This allows us to actually skip the \u0000 character instead of
interpreting it.
It is important to say that even the most recent versions of Avro do
not support parsing \u0000 characters.
Change-Id: I56dfa7f0f12979fe9705c51c751513aebce4beca
Reviewed-on: http://gerrit.cloudera.org:8080/712
Tested-by: Internal Jenkins
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Before this patch, we used to accept any query referencing complex
types, regardless of the table/partition's file format being scanned.
We would ultimately hit a DCHECK in the BE when attempting to scan
complex types of a table/partition with an unsupported format.
This patch makes queries fail gracefully during planning if a scan
would access a table/partition in a format for which we do not
support complex types.
For mixed-format partitioned Hdfs tables we perform this check
at the partition granularity, so such a table can be scanned as
long as only partitions with supported formats are accessed.
HBase tables with complex-typed columns can be scanned as long as
no complex-typed columns are accessed in the query.
Change-Id: I2fd2e386c9755faf2cfe326541698a7094fa0ffc
Reviewed-on: http://gerrit.cloudera.org:8080/705
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins
Addressed JIRAs: IMPALA-1947 and IMPALA-1813
New Feature:
Adds support for creating an Avro table without an explicit
Avro schema with the following syntax.
CREATE TABLE <table_name> column_defs STORED AS AVRO
Fixes and Improvements:
This patch fixes and unifies the logic for reconciling differences between
an Avro table's Avro Schema and its column definitions. This reconciliation
logic is executed during Impala's CREATE TABLE and when loading a table's
metadata. Impala generally performs the schema reconciliation during table
creation, but Hive does not. In many cases, Hive's CREATE TABLE stores the
original column definitions in the HMS (in the StorageDescriptor) instead
of the reconciled column definitions.
The reconciliation logic considers the field/column names and follows this
conflict resolution policy which is similar to Hive's:
Mismatched number of columns -> Prefer Avro columns.
Mismatched name/type -> Prefer Avro column, except:
A CHAR/VARCHAR column definition maps to an Avro STRING, and is preserved
as a CHAR/VARCHAR in the reconciled schema.
Behavior for TIMESTAMP:
A TIMESTAMP column definition maps to an Avro STRING and is presented as a STRING
in the reconciled schema, because Avro has no binary TIMESTAMP representation.
As a result, no Avro table may have a TIMESTAMP column (existing behavior).
Change-Id: I8457354568b6049b2dd2794b65fadc06e619d648
Reviewed-on: http://gerrit.cloudera.org:8080/550
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins
Hive allows creating Avro tables without an explicit Avro schema since 0.14.0.
For such tables, the Avro schema is inferred from the column definitions,
and not stored in the metadata at all (no Avro schema literal or Avro schema file).
This patch adds support for loading the metadata of such tables, although Impala
currently cannot create such tables (expect a follow-on patch).
Change-Id: I9e66921ffbeff7ce6db9619bcfb30278b571cd95
Reviewed-on: http://gerrit.cloudera.org:8080/538
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins
This patch corrects a mistake in the Parquet magic file number verification
and adds a test about it. Note that with this patch Impala may fail to read
Parquet files with wrong magic number that it used to read before.
Change-Id: Iff31accda1e1d541946ef1f750e38886ce4cb8d5
Reviewed-on: http://gerrit.cloudera.org:8080/515
Reviewed-by: Ippokratis Pandis <ipandis@cloudera.com>
Tested-by: Internal Jenkins
This allows to specify split keys in Kudu's CREATE TABLE statement as part
of the key/value pairs in TBLPROPERTIES.
Splits are expected to be specified in as json arrays of arrays: [[key1], [key2], ...]
'key1', 'key2 might be single values or comma separated lists of values, depending
on whether the table has a simple of compound primary key.
This also adds a series of test tables to be created for the kutu table format
when load-data.py is executed.
Change-Id: I1824199fda14abb2d7352800789f2b9c2f2124ae
Reviewed-on: http://gerrit.sjc.cloudera.com:8080/6974
Tested-by: jenkins
Reviewed-by: Martin Grund <mgrund@cloudera.com>
This adds a new TABLE_PROPERTIES section that will be included in the
CREATE TABLE statement as TBLPROPERTIES. Each line in this new section
is expected to be in the form:
<file_format>:<key>=<value>
Properties are only added to create table statements of the file format
they specify.
Change-Id: I89ef7ced3351ecf2c727050ca426f6616f3e5bcd
Reviewed-on: http://gerrit.sjc.cloudera.com:8080/6945
Tested-by: jenkins
Reviewed-by: Martin Grund <mgrund@cloudera.com>
The hardcoded timezone information is from Java version 1.7.0_76.
Change-Id: I32c40d0036473079e5bfd4d0252a648cbb0e7c23
Reviewed-on: http://gerrit.cloudera.org:8080/393
Reviewed-by: Juan Yu <jyu@cloudera.com>
Tested-by: Internal Jenkins
When running with a release build, NULL would be returned when
reading values from required fields in parquet files (with a debug
build a DCHECK would be hit).
Previously when the max definition level for a field was 0 (which
happens if a field is required), the definition level for value was
incorrectly set to 1. The max definition level is related to nested
data and is defined to be the number of nullable fields that will be
encountered when traversing a path to reach the desired end field.
For example, if a nested schema has a path a.b.c.d where b and d are
nullable then the max def level is 2. A def level is attached to each
value to indicate the number of optional values that are present (in
the previous example an def level of 2 means both b and d are not
null). So having a def level for a value that is greater than the max
def level for a field should never happen.
Change-Id: Ia91a97cf79e672c420d10416c6817f0930dcc920
(cherry picked from commit cdd67e4c7fd62d5b08adfaa303d7bb2382e6932c)
Reviewed-on: http://gerrit.cloudera.org:8080/386
Reviewed-by: Casey Ching <casey@cloudera.com>
Tested-by: Internal Jenkins
This patch fixes an issue when an uninitialized, empty row is falsely
added to the rowbatch. The uninitialized data inside this row leads
later on to a crash when the null byte is checked together with the
offsets (that contains garbage).
The fix is to not only check for the number of materialized columns, but
as well for the number of materialized partition key columns. Only if both are
empty and the parser has an unfinished tuple, add the empty row.
To accommodate for the last row, check in FinishScanRange() if there is an
unfinished tuple with materialized slots or materialized partition key. Write
the fields if necessary.
Change-Id: I2808cc228e62d048d917d3a6352d869d117597ab
(cherry picked from commit c1795a8b40d10fbb32d9051a0e7de5ebffc8a6bd)
Reviewed-on: http://gerrit.cloudera.org:8080/364
Reviewed-by: Juan Yu <jyu@cloudera.com>
Tested-by: Internal Jenkins
This patch adds analysis support for the following new constructs.
Struct-field references:
Dot-separated paths such as "tblalias.col.field1.field2..." can now be used
to access fields of a struct. Such struct-field SlotRefs show up as new slot
in the tuple descriptor of the parent table.
Collection table references:
A collection-typed column or field can be referenced as a table in the FROM
clause using a dot-separated path, e.g., "FROM db.tbl.array_col". This exposes
the collection's fields as a table whose columns can be referenced as usual.
Collections referenced this way are flattened during execution. The following
subsections explain the analysis behavior in more detail:
Aliases:
Collection table references can either have an explicit alias a single
implicit alias. Examples:
SELECT ... FROM db.tbl.array_col AS a
-> explicit alias 'a'
SELECT ... FROM db.tbl.array_col
-> implicit alias 'array_col'
Flattening of collections:
Collection table refs can refer to table aliases defined to their left
in the same select block. References linked in this way indicate an implicit
parent/child join. Example:
SELECT parent.id, child.item FROM db.tbl parent, parent.array_col child
The aliases 'parent' and 'child' can be used to access the columns of 'tbl' and
the fields of 'array_col', respectively. In the flattened result set, collection
items implicitly join with parent rows iff the collection row is nested within
the parent.
The following stmt is not an implicit join, but a scan of a nested collection.
SELECT db.tbl.map_col.value FROM db.tbl.map_col
The following stmt is not a parent/child join but a cartesian product
because the collection does not reference an existing table alias.
SELECT a.id, map_col.value FROM db.tbl a, db.tbl.map_col
Collection 'table' field names:
Structs have explicit field names, but collections generally do not. This patch
uses fixed implicit field names such as "item" for arrays and "key"/"value"
for maps. If an array or map has a struct element/value then the struct's fields
are also accessible without the "item"/"value" indirection.
Analysis prevents complex-typed exprs from appearing in the select list of any
query statement because it's not yet clear how to present them to a consumer
of the query results.
To keep things simple, I've deliberately left these work items for
follow-on patches:
1. analysis of correlated inline views to handle queries like:
SELECT cnt FROM customers c (SELECT COUNT(1) FROM c.orders) v
2. generalized expression substitution to handle cases like:
SELECT x.c.d FROM (SELECT a.b x FROM tbl)
Change-Id: I5f52f083bcf7056d5bfd21cc784133edb7e82ef2
Reviewed-on: http://gerrit.cloudera.org:8080/43
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins
While cherry-picking commit c289974 from cdh5-2.2.0_5.4.x, a line that causes a dataset
change was somehow missed by git's cherry-pick. This patch adds that line back in.
Change-Id: Id163643c55d44fe6a9503b54397f1f370b198554
I did a local benchmark and there's minimal performance impact(<1%)
Change-Id: I8d84a145acad886c52587258b27d33cff96ea399
(cherry picked from commit 7e750ad5d90007cc85ebe493af4dce7a537ad7c0)
Reviewed-on: http://gerrit.cloudera.org:8080/189
Reviewed-by: Juan Yu <jyu@cloudera.com>
Tested-by: Internal Jenkins
We used mkdir without a -p to load a hive13 parquet table. This failed when trying to load
the metadata, which is necessary for changes that mutate the warehouse snapshot. With this
change, it now passes.
Change-Id: Id163643c55d44fe6a9503b54397f1f370b198554
No changes to writing were made. No changes to reading Impala written
files were made.
Hive writes TIMESTAMP values to parquet files differently than Impala
does. Hive converts the value from local time to UTC before writing;
Impala does not. This change adds a startup flag that will convert UTC
to local when reading files written by Hive.
The Hive-file detection actually checks for "parquet-mr" (which is the
library Hive uses) in the file metadata. A slight possibility exists
that TIMESTAMP values written by something other than Hive but also
using parquet-mr may become incorrect. The possibility should be very
small because TIMESTAMP values are stored and encoded in a non-standard
way other applications are unlikely to be aware of.
Flags from be/src/exec/hdfs-parquet-scanner.cc:
-convert_legacy_hive_parquet_utc_timestamps (When true, TIMESTAMPs
read from files written by Parquet-MR (used by Hive) will be
converted from UTC to local time. Writes are unaffected.) type: bool
default: false
Change-Id: I79a499fe24049b7025ee2dd76c9c3e07010d346a
Reviewed-on: http://gerrit.cloudera.org:8080/35
Reviewed-by: Casey Ching <casey@cloudera.com>
Tested-by: Internal Jenkins
DistributedFileSystem is lenient about seeking past the end of the file.
Other FileSystem implementations, such as NativeS3FileSystem, return an
error on this condition. That leads to a scary looking message in the
query warnings.
So, when creating scan ranges, let's require that the ranges fall within
the file bounds (at least according to what the HdfsFileDesc indicates
is the length). There were a couple of kinds of AllocateScanRange()
callsites that needed to be fixed up:
1) When a stream wants to read past a scan range, be careful not to read
past the end of the file.
2) When Impala needs to "guess" at the length of a range, use the
file_length as an upper bound on the guess. We were already doing this
someplaces but not everywhere.
3) When the scan range is derived from parquet metadata, validate the
metadata against file_length and issue appropriate errors. This will
give better diagnostics for corrupt files.
Note that we can't rely on this for safety (HdfsFileDesc file_length may
be stale), but it does mean that when metadata is up-to-date Impala will
no longer try to access beyond the end of files (and so we'll no longer
get false positive errors from the filesystem).
Additionally, this change revealed a pre-existing problem with files
that have multiple row-groups. The first time through InitColumns(),
stream_ was set to NULL. But, stream_->filename could potentially be
accessed when constructing error statuses for subsequent row-groups.
Change-Id: Ia668fa8c261547f85a18a96422846edcea57043e
Reviewed-on: http://gerrit.sjc.cloudera.com:8080/5424
Reviewed-by: Daniel Hecht <dhecht@cloudera.com>
Tested-by: 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
Fixed a bug when setting the length in reading/write text files for CHAR(N).
Also added chars_tiny table for testing CHAR(N) and VARCHAR(N).
Change-Id: If5d5db30afa4b00cf03c68c6a845f182970329f4
Reviewed-on: http://gerrit.sjc.cloudera.com:8080/4415
Reviewed-by: Victor Bittorf <victor.bittorf@cloudera.com>
Tested-by: jenkins
Changes include:
* Fix compile errors due to new column stats API and other stats related
fixes.
* Temporarily disable JDBC tests due to new serialization format in Hive .13
* Disable view compatibility tests until we can get them to work in Hive .13
* Test fixes due to Hive's type checking for partition column values
Change-Id: I05cc6a95976e0e037be79d91bc330a06d2fdc46c
