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Proposed changes
Doris's Routine Load realizes the import of data from Kafka to Doris, and make a feature of real-time synchronization of data from Pulsar to Doris based on Pulsar IO.
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The custom abstract class DorisAbstractSink implements the interface org.apache.pulsar.io.core.Sink.
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The DorisGenericRecordSink class inherits the abstract class DorisAbstractSink, and the speci
Use case:
Add the ability to search for an element in an array and retrieve back the array index.
As per the PostgreSQL documentation:
array_position ( anycompatiblearray, anycompatible [, integer ] ) → integer
Returns the subscript of the first occurrence of the second argument in the array, or NULL if it's not present
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Hey everyone!
mapd-core-cpu is already available on conda-forge (https://anaconda.org/conda-forge/omniscidb-cpu)
now we should add some instructions on the documentation.
at this moment it is available for linux and osx.
some additional information about the configuration:
- for now, always install
omniscidb-cpuinside a conda environment (also it is a good practice), eg:
StarRocks is compiled using c++17, so instead of relying on boost::variant, we can use std::variant.
This is a very simple issue, you can try this modification
Is your feature request related to a problem or challenge? Please describe what you are trying to do.
The doc site https://arrow.apache.org/datafusion/ is the public face of DataFusion. While it currently has a great foundation / layout, the content is a bit out of date (and could always use more love)
Making DataFusion more accessible to new users would be great way to get involved with t
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not elegant
> create table x (x int)
created
> insert into x values (1)
1 rows inserted
> insert into x values (2)
1 rows inserted
> insert into x values (33333)
1 rows inserted
> select * from x;
+---+
| x |
+---+
| 1 |
+---+
+---+
| 2 |
+---+
+-------+
| 33333 |
+-------+
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AOE v0.1.0 limitations:
- AOE has a global hard limit of ? table count.
- AOE has a hard limit of ? columns per table.
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In Big Query there is a function array_concat_agg that aggregates array fields by concatenating the arrays. In Snowflake there is a flatten function that can unnest nested arrays into single array. I am looking for similar functionality in duckdb.
select flatten([[1, 2], [2, 3], [4, 5]]would return[1, 2, 2, 3, 4, 5]I would also need a distinct option:
`select flatten(DISTINCT [[1, 2],