You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@fluss.apache.org by "caozhen1937 (via GitHub)" <gi...@apache.org> on 2025/09/11 15:53:14 UTC
[PR] [docs] Update datalake related doc for support iceberg and lance [fluss]
caozhen1937 opened a new pull request, #1686:
URL: https://github.com/apache/fluss/pull/1686
<!--
*Thank you very much for contributing to Fluss - we are happy that you want to help us improve Fluss. To help the community review your contribution in the best possible way, please go through the checklist below, which will get the contribution into a shape in which it can be best reviewed.*
## Contribution Checklist
- Make sure that the pull request corresponds to a [GitHub issue](https://github.com/apache/fluss/issues). Exceptions are made for typos in JavaDoc or documentation files, which need no issue.
- Name the pull request in the format "[component] Title of the pull request", where *[component]* should be replaced by the name of the component being changed. Typically, this corresponds to the component label assigned to the issue (e.g., [kv], [log], [client], [flink]). Skip *[component]* if you are unsure about which is the best component.
- Fill out the template below to describe the changes contributed by the pull request. That will give reviewers the context they need to do the review.
- Make sure that the change passes the automated tests, i.e., `mvn clean verify` passes.
- Each pull request should address only one issue, not mix up code from multiple issues.
**(The sections below can be removed for hotfixes or typos)**
-->
### Purpose
<!-- Linking this pull request to the issue -->
Linked issue: close #1602
<!-- What is the purpose of the change -->
### Brief change log
<!-- Please describe the changes made in this pull request and explain how they address the issue -->
### Tests
<!-- List UT and IT cases to verify this change -->
### API and Format
<!-- Does this change affect API or storage format -->
### Documentation
<!-- Does this change introduce a new feature -->
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: issues-unsubscribe@fluss.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
Re: [PR] [docs] Update datalake related doc for support iceberg and lance [fluss]
Posted by "luoyuxia (via GitHub)" <gi...@apache.org>.
luoyuxia merged PR #1686:
URL: https://github.com/apache/fluss/pull/1686
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: issues-unsubscribe@fluss.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
Re: [PR] [docs] Update datalake related doc for support iceberg and lance [fluss]
Posted by "luoyuxia (via GitHub)" <gi...@apache.org>.
luoyuxia commented on code in PR #1686:
URL: https://github.com/apache/fluss/pull/1686#discussion_r2342827044
##########
website/docs/quickstart/flink.md:
##########
@@ -346,10 +346,13 @@ The following SQL query should return an empty result.
SELECT * FROM fluss_customer WHERE `cust_key` = 1;
```
-## Integrate with Paimon
+## Integrate with Data Lake
Review Comment:
Also. not change this doc. Mixing other lake formats make it hard to follow. We can have a seperate doc for iceberg.
##########
website/docs/install-deploy/overview.md:
##########
@@ -117,7 +117,8 @@ We have listed them in the table below the figure.
</td>
<td>
<li>[Paimon](maintenance/tiered-storage/lakehouse-storage.md)</li>
Review Comment:
update all to
```
<li>[Paimon](streaming-lakehouse/integrate-data-lakes/paimon.md)</li>
<li>[Iceberg](streaming-lakehouse/integrate-data-lakes/iceberg.md)</li>
<li>[Lance](streaming-lakehouse/integrate-data-lakes/lance.md)</li>
```
##########
website/docs/maintenance/tiered-storage/lakehouse-storage.md:
##########
@@ -45,8 +45,10 @@ datalake.paimon.uri: thrift://<hive-metastore-host-name>:<port>
datalake.paimon.warehouse: hdfs:///path/to/warehouse
```
#### Add other jars required by datalake
-While Fluss includes the core Paimon library, additional jars may still need to be manually added to `${FLUSS_HOME}/plugins/paimon/` according to your needs.
-For example, for OSS filesystem support, you need to put `paimon-oss-<paimon_version>.jar` into directory `${FLUSS_HOME}/plugins/paimon/`.
+While Fluss includes the core libraries for supported data lake formats, additional jars may still need to be manually added according to your needs.
+For Paimon: Put additional jars into `${FLUSS_HOME}/plugins/paimon/`, e.g., for OSS filesystem support, put `paimon-oss-<paimon_version>.jar`
Review Comment:
Not change this doc. I don't want to mix other formats in this doc since it'll make it hard to follow this guidance.
##########
website/docs/maintenance/tiered-storage/lakehouse-storage.md:
##########
@@ -58,10 +60,17 @@ Then, you must start the datalake tiering service to tier Fluss's data to the la
- Put [fluss-flink connector jar](/downloads) into `${FLINK_HOME}/lib`, you should choose a connector version matching your Flink version. If you're using Flink 1.20, please use [fluss-flink-1.20-$FLUSS_VERSION$.jar](https://repo1.maven.org/maven2/org/apache/fluss/fluss-flink-1.20/$FLUSS_VERSION$/fluss-flink-1.20-$FLUSS_VERSION$.jar)
- If you are using [Amazon S3](http://aws.amazon.com/s3/), [Aliyun OSS](https://www.aliyun.com/product/oss) or [HDFS(Hadoop Distributed File System)](https://hadoop.apache.org/docs/stable/) as Fluss's [remote storage](maintenance/tiered-storage/remote-storage.md),
you should download the corresponding [Fluss filesystem jar](/downloads#filesystem-jars) and also put it into `${FLINK_HOME}/lib`
-- Put [fluss-lake-paimon jar](https://repo1.maven.org/maven2/org/apache/fluss/fluss-lake-paimon/$FLUSS_VERSION$/fluss-lake-paimon-$FLUSS_VERSION$.jar) into `${FLINK_HOME}/lib`
+- For Paimon integration:
Review Comment:
dito. Not change this for it make hard to follow
##########
website/docs/maintenance/configuration.md:
##########
@@ -163,9 +163,9 @@ during the Fluss cluster working.
## Lakehouse
-| Option | Type | Default | Description |
-|-----------------|------|---------|---------------------------------------------------------------------------------------------------------------------------|
-| datalake.format | Enum | (None) | The datalake format used by of Fluss to be as lakehouse storage, such as Paimon, Iceberg, Hudi. Now, only support Paimon. |
+| Option | Type | Default | Description |
+|-----------------|------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| datalake.format | Enum | (None) | The datalake format used by of Fluss to be as lakehouse storage. Currently, supported formats are Paimon, Iceberg, and Lance. In the future, more kinds of data lake format will be supported, such as DeltaLake or Hudi. |
Review Comment:
Also to update it in `ConfigOptions`
##########
website/docs/engine-flink/options.md:
##########
@@ -60,29 +60,29 @@ ALTER TABLE log_table SET ('table.log.ttl' = '7d');
## Storage Options
-| Option | Type | Default | Description |
-|-----------------------------------------|----------|-------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| bucket.num | int | The bucket number of Fluss cluster. | The number of buckets of a Fluss table. |
-| bucket.key | String | (None) | Specific the distribution policy of the Fluss table. Data will be distributed to each bucket according to the hash value of bucket-key (It must be a subset of the primary keys excluding partition keys of the primary key table). If you specify multiple fields, delimiter is `,`. If the table has a primary key and a bucket key is not specified, the bucket key will be used as primary key(excluding the partition key). If the table has no primary key and the bucket key is not specified, the data will be distributed to each bucket randomly. |
-| table.log.ttl | Duration | 7 days | The time to live for log segments. The configuration controls the maximum time we will retain a log before we will delete old segments to free up space. If set to -1, the log will not be deleted. |
-| table.auto-partition.enabled | Boolean | false | Whether enable auto partition for the table. Disable by default. When auto partition is enabled, the partitions of the table will be created automatically. |
-| table.auto-partition.key | String | (None) | This configuration defines the time-based partition key to be used for auto-partitioning when a table is partitioned with multiple keys. Auto-partitioning utilizes a time-based partition key to handle partitions automatically, including creating new ones and removing outdated ones, by comparing the time value of the partition with the current system time. In the case of a table using multiple partition keys (such as a composite partitioning strategy), this feature determines which key should serve as the primary time dimension for making auto-partitioning decisions. And If the table has only one partition key, this config is not necessary. Otherwise, it must be specified. |
-| table.auto-partition.time-unit | ENUM | DAY | The time granularity for auto created partitions. The default value is `DAY`. Valid values are `HOUR`, `DAY`, `MONTH`, `QUARTER`, `YEAR`. If the value is `HOUR`, the partition format for auto created is yyyyMMddHH. If the value is `DAY`, the partition format for auto created is yyyyMMdd. If the value is `MONTH`, the partition format for auto created is yyyyMM. If the value is `QUARTER`, the partition format for auto created is yyyyQ. If the value is `YEAR`, the partition format for auto created is yyyy. |
-| table.auto-partition.num-precreate | Integer | 2 | The number of partitions to pre-create for auto created partitions in each check for auto partition. For example, if the current check time is 2024-11-11 and the value is configured as 3, then partitions 20241111, 20241112, 20241113 will be pre-created. If any one partition exists, it'll skip creating the partition. The default value is 2, which means 2 partitions will be pre-created. If the `table.auto-partition.time-unit` is `DAY`(default), one precreated partition is for today and another one is for tomorrow. For a partition table with multiple partition keys, pre-create is unsupported and will be set to 0 automatically when creating table if it is not explicitly specified. |
-| table.auto-partition.num-retention | Integer | 7 | The number of history partitions to retain for auto created partitions in each check for auto partition. For example, if the current check time is 2024-11-11, time-unit is DAY, and the value is configured as 3, then the history partitions 20241108, 20241109, 20241110 will be retained. The partitions earlier than 20241108 will be deleted. The default value is 7, which means that 7 partitions will be retained. |
-| table.auto-partition.time-zone | String | the system time zone | The time zone for auto partitions, which is by default the same as the system time zone. |
-| table.replication.factor | Integer | (None) | The replication factor for the log of the new table. When it's not set, Fluss will use the cluster's default replication factor configured by default.replication.factor. It should be a positive number and not larger than the number of tablet servers in the Fluss cluster. A value larger than the number of tablet servers in Fluss cluster will result in an error when the new table is created. |
-| table.log.format | Enum | ARROW | The format of the log records in log store. The default value is `ARROW`. The supported formats are `ARROW` and `INDEXED`. |
-| table.log.arrow.compression.type | Enum | ZSTD | The compression type of the log records if the log format is set to `ARROW`. The candidate compression type is `NONE`, `LZ4_FRAME`, `ZSTD`. The default value is `ZSTD`. |
-| table.log.arrow.compression.zstd.level | Integer | 3 | The compression level of the log records if the log format is set to `ARROW` and the compression type is set to `ZSTD`. The valid range is 1 to 22. The default value is 3. |
-| table.kv.format | Enum | COMPACTED | The format of the kv records in kv store. The default value is `COMPACTED`. The supported formats are `COMPACTED` and `INDEXED`. |
-| table.log.tiered.local-segments | Integer | 2 | The number of log segments to retain in local for each table when log tiered storage is enabled. It must be greater that 0. The default is 2. |
-| table.datalake.enabled | Boolean | false | Whether enable lakehouse storage for the table. Disabled by default. When this option is set to ture and the datalake tiering service is up, the table will be tiered and compacted into datalake format stored on lakehouse storage. |
-| table.datalake.format | Enum | (None) | The data lake format of the table specifies the tiered Lakehouse storage format, such as Paimon, Iceberg, DeltaLake, or Hudi. Currently, only `paimon` is supported. Once the `table.datalake.format` property is configured, Fluss adopts the key encoding and bucketing strategy used by the corresponding data lake format. This ensures consistency in key encoding and bucketing, enabling seamless **Union Read** functionality across Fluss and Lakehouse. The `table.datalake.format` can be pre-defined before enabling `table.datalake.enabled`. This allows the data lake feature to be dynamically enabled on the table without requiring table recreation. If `table.datalake.format` is not explicitly set during table creation, the table will default to the format specified by the `datalake.format` configuration in the Fluss cluster |
-| table.datalake.freshness | Duration | 3min | It defines the maximum amount of time that the datalake table's content should lag behind updates to the Fluss table. Based on this target freshness, the Fluss service automatically moves data from the Fluss table and updates to the datalake table, so that the data in the datalake table is kept up to date within this target. If the data does not need to be as fresh, you can specify a longer target freshness time to reduce costs. |
-| table.datalake.auto-compaction | Boolean | false | If true, compaction will be triggered automatically when tiering service writes to the datalake. It is disabled by default. |
-| table.merge-engine | Enum | (None) | Defines the merge engine for the primary key table. By default, primary key table uses the [default merge engine(last_row)](table-design/table-types/pk-table/merge-engines/default.md). It also supports two merge engines are `first_row` and `versioned`. The [first_row merge engine](table-design/table-types/pk-table/merge-engines/first-row.md) will keep the first row of the same primary key. The [versioned merge engine](table-design/table-types/pk-table/merge-engines/versioned.md) will keep the row with the largest version of the same primary key. |
-| table.merge-engine.versioned.ver-column | String | (None) | The column name of the version column for the `versioned` merge engine. If the merge engine is set to `versioned`, the version column must be set. |
+| Option | Type | Default | Description |
+|-----------------------------------------|----------|-------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| bucket.num | int | The bucket number of Fluss cluster. | The number of buckets of a Fluss table. |
+| bucket.key | String | (None) | Specific the distribution policy of the Fluss table. Data will be distributed to each bucket according to the hash value of bucket-key (It must be a subset of the primary keys excluding partition keys of the primary key table). If you specify multiple fields, delimiter is `,`. If the table has a primary key and a bucket key is not specified, the bucket key will be used as primary key(excluding the partition key). If the table has no primary key and the bucket key is not specified, the data will be distributed to each bucket randomly. |
+| table.log.ttl | Duration | 7 days | The time to live for log segments. The configuration controls the maximum time we will retain a log before we will delete old segments to free up space. If set to -1, the log will not be deleted. |
+| table.auto-partition.enabled | Boolean | false | Whether enable auto partition for the table. Disable by default. When auto partition is enabled, the partitions of the table will be created automatically. |
+| table.auto-partition.key | String | (None) | This configuration defines the time-based partition key to be used for auto-partitioning when a table is partitioned with multiple keys. Auto-partitioning utilizes a time-based partition key to handle partitions automatically, including creating new ones and removing outdated ones, by comparing the time value of the partition with the current system time. In the case of a table using multiple partition keys (such as a composite partitioning strategy), this feature determines which key should serve as the primary time dimension for making auto-partitioning decisions. And If the table has only one partition key, this config is not necessary. Otherwise, it must be specified. |
+| table.auto-partition.time-unit | ENUM | DAY | The time granularity for auto created partitions. The default value is `DAY`. Valid values are `HOUR`, `DAY`, `MONTH`, `QUARTER`, `YEAR`. If the value is `HOUR`, the partition format for auto created is yyyyMMddHH. If the value is `DAY`, the partition format for auto created is yyyyMMdd. If the value is `MONTH`, the partition format for auto created is yyyyMM. If the value is `QUARTER`, the partition format for auto created is yyyyQ. If the value is `YEAR`, the partition format for auto created is yyyy. |
+| table.auto-partition.num-precreate | Integer | 2 | The number of partitions to pre-create for auto created partitions in each check for auto partition. For example, if the current check time is 2024-11-11 and the value is configured as 3, then partitions 20241111, 20241112, 20241113 will be pre-created. If any one partition exists, it'll skip creating the partition. The default value is 2, which means 2 partitions will be pre-created. If the `table.auto-partition.time-unit` is `DAY`(default), one precreated partition is for today and another one is for tomorrow. For a partition table with multiple partition keys, pre-create is unsupported and will be set to 0 automatically when creating table if it is not explicitly specified. |
+| table.auto-partition.num-retention | Integer | 7 | The number of history partitions to retain for auto created partitions in each check for auto partition. For example, if the current check time is 2024-11-11, time-unit is DAY, and the value is configured as 3, then the history partitions 20241108, 20241109, 20241110 will be retained. The partitions earlier than 20241108 will be deleted. The default value is 7, which means that 7 partitions will be retained. |
+| table.auto-partition.time-zone | String | the system time zone | The time zone for auto partitions, which is by default the same as the system time zone. |
+| table.replication.factor | Integer | (None) | The replication factor for the log of the new table. When it's not set, Fluss will use the cluster's default replication factor configured by default.replication.factor. It should be a positive number and not larger than the number of tablet servers in the Fluss cluster. A value larger than the number of tablet servers in Fluss cluster will result in an error when the new table is created. |
+| table.log.format | Enum | ARROW | The format of the log records in log store. The default value is `ARROW`. The supported formats are `ARROW` and `INDEXED`. |
+| table.log.arrow.compression.type | Enum | ZSTD | The compression type of the log records if the log format is set to `ARROW`. The candidate compression type is `NONE`, `LZ4_FRAME`, `ZSTD`. The default value is `ZSTD`. |
+| table.log.arrow.compression.zstd.level | Integer | 3 | The compression level of the log records if the log format is set to `ARROW` and the compression type is set to `ZSTD`. The valid range is 1 to 22. The default value is 3. |
+| table.kv.format | Enum | COMPACTED | The format of the kv records in kv store. The default value is `COMPACTED`. The supported formats are `COMPACTED` and `INDEXED`. |
+| table.log.tiered.local-segments | Integer | 2 | The number of log segments to retain in local for each table when log tiered storage is enabled. It must be greater that 0. The default is 2. |
+| table.datalake.enabled | Boolean | false | Whether enable lakehouse storage for the table. Disabled by default. When this option is set to ture and the datalake tiering service is up, the table will be tiered and compacted into datalake format stored on lakehouse storage. |
+| table.datalake.format | Enum | (None) | The data lake format of the table specifies the tiered Lakehouse storage format. Currently, supported formats are `paimon`, `iceberg`, and `lance`. In the future, more kinds of data lake format will be supported, such as DeltaLake or Hudi. Once the `table.datalake.format` property is configured, Fluss adopts the key encoding and bucketing strategy used by the corresponding data lake format. This ensures consistency in key encoding and bucketing, enabling seamless **Union Read** functionality across Fluss and Lakehouse. The `table.datalake.format` can be pre-defined before enabling `table.datalake.enabled`. This allows the data lake feature to be dynamically enabled on the table without requiring table recreation. If `table.datalake.format` is not explicitly set during table creation, the table will default to the format specified by the `datalake.format` configuration in the Fluss cluster. |
Review Comment:
Also to update it in ConfigOptions
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: issues-unsubscribe@fluss.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
Re: [PR] [docs] Update datalake related doc for support iceberg and lance [fluss]
Posted by "luoyuxia (via GitHub)" <gi...@apache.org>.
luoyuxia commented on code in PR #1686:
URL: https://github.com/apache/fluss/pull/1686#discussion_r2342874680
##########
fluss-common/src/main/java/org/apache/fluss/config/ConfigOptions.java:
##########
@@ -1640,8 +1641,8 @@ public class ConfigOptions {
.enumType(DataLakeFormat.class)
.noDefaultValue()
.withDescription(
- "The datalake format used by Fluss to be as lake storage, such as Paimon, Iceberg, Hudi. "
- + "Now, only support Paimon.");
+ "The datalake format used by of Fluss to be as lakehouse storage. Currently, supported formats are Paimon, Iceberg, and Lance. "
+ + "In the future, more kinds of data lake format will be supported, such as DeltaLake or Hudi. ");
Review Comment:
dito
##########
fluss-common/src/main/java/org/apache/fluss/config/ConfigOptions.java:
##########
@@ -1293,11 +1293,12 @@ public class ConfigOptions {
.enumType(DataLakeFormat.class)
.noDefaultValue()
.withDescription(
- "The data lake format of the table specifies the tiered Lakehouse storage format, such as Paimon, Iceberg, DeltaLake, or Hudi. Currently, only `paimon` is supported. "
+ "The data lake format of the table specifies the tiered Lakehouse storage format. Currently, supported formats are `paimon`, `iceberg`, and `lance`. "
+ + "In the future, more kinds of data lake format will be supported, such as DeltaLake or Hudi. "
+ "Once the `table.datalake.format` property is configured, Fluss adopts the key encoding and bucketing strategy used by the corresponding data lake format. "
+ "This ensures consistency in key encoding and bucketing, enabling seamless **Union Read** functionality across Fluss and Lakehouse. "
+ "The `table.datalake.format` can be pre-defined before enabling `table.datalake.enabled`. This allows the data lake feature to be dynamically enabled on the table without requiring table recreation. "
- + "If `table.datalake.format` is not explicitly set during table creation, the table will default to the format specified by the `datalake.format` configuration in the Fluss cluster.");
+ + "If `table.datalake.format` is not explicitly set during table creation, the table will default to the format specified by the `datalake.format` configuration in the Fluss cluster. ");
Review Comment:
nit:
remove the blank at the end
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: issues-unsubscribe@fluss.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
Re: [PR] [docs] Update datalake related doc for support iceberg and lance [fluss]
Posted by "caozhen1937 (via GitHub)" <gi...@apache.org>.
caozhen1937 commented on PR #1686:
URL: https://github.com/apache/fluss/pull/1686#issuecomment-3281575341
I verified it using the AI tool and found no new areas that needed to be modified.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: issues-unsubscribe@fluss.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
Re: [PR] [docs] Update datalake related doc for support iceberg and lance [fluss]
Posted by "caozhen1937 (via GitHub)" <gi...@apache.org>.
caozhen1937 commented on code in PR #1686:
URL: https://github.com/apache/fluss/pull/1686#discussion_r2342838843
##########
website/docs/maintenance/configuration.md:
##########
@@ -163,9 +163,9 @@ during the Fluss cluster working.
## Lakehouse
-| Option | Type | Default | Description |
-|-----------------|------|---------|---------------------------------------------------------------------------------------------------------------------------|
-| datalake.format | Enum | (None) | The datalake format used by of Fluss to be as lakehouse storage, such as Paimon, Iceberg, Hudi. Now, only support Paimon. |
+| Option | Type | Default | Description |
+|-----------------|------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| datalake.format | Enum | (None) | The datalake format used by of Fluss to be as lakehouse storage. Currently, supported formats are Paimon, Iceberg, and Lance. In the future, more kinds of data lake format will be supported, such as DeltaLake or Hudi. |
Review Comment:
Sorry. I forget descripe in code
##########
website/docs/maintenance/configuration.md:
##########
@@ -163,9 +163,9 @@ during the Fluss cluster working.
## Lakehouse
-| Option | Type | Default | Description |
-|-----------------|------|---------|---------------------------------------------------------------------------------------------------------------------------|
-| datalake.format | Enum | (None) | The datalake format used by of Fluss to be as lakehouse storage, such as Paimon, Iceberg, Hudi. Now, only support Paimon. |
+| Option | Type | Default | Description |
+|-----------------|------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| datalake.format | Enum | (None) | The datalake format used by of Fluss to be as lakehouse storage. Currently, supported formats are Paimon, Iceberg, and Lance. In the future, more kinds of data lake format will be supported, such as DeltaLake or Hudi. |
Review Comment:
Sorry. I forget describe in code
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: issues-unsubscribe@fluss.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org