Thanks all for your discussion.
The Apache Paimon community is also considering support for this
Variant type, without a doubt, we hope to maintain consistency with
Iceberg.
Not only the Paimon community, but also various computing engines need
to adapt to this type, such as Flink and StarRocks.
Hi,
+1 to Jean-Baptiste.
I am not a PMC member, but what I see in the iceberg community is
Ryan's dedication to making this community better. He has invested a
lot of energy in the community. I have also learned a lot from him.
I personally trust Ryan, and I don't think he would do anything that
+1
1. Download the source tarball, signature (.asc), and checksum (.sha512):
OK
2. Import gpg keys: download KEYS and run gpg --import
/path/to/downloaded/KEYS (optional if this hasn’t changed) : OK
3. Verify the signature by running: gpg --verify
apache-iceberg-xx.tar.gz.asc: OK
4. Verify the
+1
1. Download the source tarball, signature (.asc), and checksum (.sha512):
OK
2. Import gpg keys: download KEYS and run gpg --import
/path/to/downloaded/KEYS (optional if this hasn’t changed) : OK
3. Verify the signature by running: gpg --verify
apache-iceberg-xx-incubating.tar.gz.asc: OK
4.
+ @Kun Liu
Best,
Jingsong
On Thu, Sep 24, 2020 at 11:33 AM Junjie Chen
wrote:
> Hi Kun
>
> I think you want to send mail to dev-subscr...@iceberg.apache.org.
>
> On Thu, Sep 24, 2020 at 11:25 AM Kun Liu wrote:
>
>> Hi，
>>
>> subscribe to the dev mail list.
>>
>> Best,
>> Kun Liu
>>
>
>
> --
>
+1
Thanks Ryan for reporting.
On Wed, Sep 9, 2020 at 3:59 AM Ryan Blue wrote:
> Hi everyone,
>
> It’s time for our board report, which I think is the last monthly report.
> Here’s what I have so far. Please comment and reply with anything that I’ve
> missed!
>
> rb
> Description:
>
> Apache Ice
+1 for timestamps are linear, in implementation, maybe the writer only
needs to look at the previous snapshot timestamp.
We're trying to think of iceberg as a message queue, Let's take the popular
queue Kafka as an example,
Iceberg has snapshotId and timestamp, corresponding, Kafka has offset and
+1 for `iceberg-hive-metastore`
I'm confused about `iceberg-hive` and `iceberg-mr`.
Best,
Jingsong
On Thu, Aug 20, 2020 at 9:48 AM Dongjoon Hyun
wrote:
> +1 for `iceberg-hive-metastore`.
>
> Maybe, is `Apache Iceberg 1.0.0` a good candidate to have that breaking
> change?
>
> Bests,
> Dongjoon
Thanks Jungtaek for starting this discussion.
What our team wants to do is data ingest into the Iceberg table with one
minute frequency. This frequency can also lead to a large number of small
files.
Auto compaction(rewrites manifest and data files) in the streaming
sink(writer) looks wonderful.
Congratulations Shardul! Well deserved!
Best,
Jingsong
On Thu, Jul 23, 2020 at 7:27 AM Anton Okolnychyi
wrote:
> Congrats and welcome! Keep up the good work!
>
> - Anton
>
> On 22 Jul 2020, at 16:02, RD wrote:
>
> Congratulations Shardul! Well deserved!
>
> -Best,
> R.
>
> On Wed, Jul 22, 2020
> scan);
>>> }
>>> }
>>>
>>> return tasks;
>>> }
>>>
>>>
>>> On Fri, Jul 17, 2020 at 9:35 AM Sud wrote:
>>>
>>>> Thanks @Jingsong for reply
>>>>
>>>> Yes one additio
Hi Sud,
The batch read of the Iceberg table should just read the latest snapshot.
I think this case is that your large tables have a large number of manifest
files.
1.The simple way is reducing manifest file numbers:
- For reducing manifest file number, you can try
`Actions.rewriteManifests`(Than
Hi Ashish,
Here is my thinking:
IIUC, Spark Writer (Record writer) also buffer files as Iceberg dataFiles,
for every micro-batch, Spark:
- Closes DataFiles in the end (One task one file at least if task has
records)
- Collect them into Driver side, do a snapshot commit.
So, you can choose the tr
+1 (non-binding)
- verified signature and checksum
- built from source and run tests
- Validated Spark3: Used Ryan's example command, played with Spark3, looks
very good.
- Validated vectorized reads: open vectorization-enabled, works well.
Best,
Jingsong
On Mon, Jul 13, 2020 at 2:37 PM Gautam
Hi,
When I look at the issues, it is difficult for me to determine which ones
are already in progress and how they were fixed.
And for understanding an issue, it seems that I need to read the
discussion in issue, then search and find the merged pull request. It is
not convenient.
Can community ma
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