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[GitHub] [iceberg] polaris6 opened a new pull request #4463: Docs: update Spark Write doc for partitioned tables
polaris6 opened a new pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463
I am using spark sql to write data, the amount of data is very large, so I don't want to sort the data globally, but I didn't find an example of partial sorting in the documentation, I want to add it here, thanks!
Sort by definition in spark sql documentation:
https://spark.apache.org/docs/latest/sql-ref-syntax-qry-select-sortby.html
<img width="812" alt="image" src="https://user-images.githubusercontent.com/29967142/161223329-0a593296-049f-4d21-ba02-d7711259d83b.png">
The test:
The first step is to create a table:
<img width="762" alt="wecom-temp-0f83c792cf74f323d1f2dc9431255605" src="https://user-images.githubusercontent.com/29967142/161223676-d070a45a-6180-4641-a52f-651f41db90c9.png">
Then query the data by sort by:
<img width="863" alt="wecom-temp-7a6e180f1068256a1eb80b87156a8bf6" src="https://user-images.githubusercontent.com/29967142/161223812-7d89515f-6538-4f7d-91c8-1a8c32c105d6.png">
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[GitHub] [iceberg] openinx commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
openinx commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r841027668
##########
File path: docs/spark/spark-writes.md
##########
@@ -311,7 +311,9 @@ distribution & sort order to Spark.
{{< /hint >}}
{{< hint info >}}
-Both global sort (`orderBy`/`sort`) and local sort (`sortWithinPartitions`) work for the requirement.
+With SQL, you can use `ORDER BY` to achieve global sorting or `SORT BY` to achieve local sorting.
Review comment:
Could you please add the `ORDER BY` and `SORT BY` links from apache spark pages ?
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[GitHub] [iceberg] polaris6 commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
polaris6 commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r841054216
##########
File path: docs/spark/spark-writes.md
##########
@@ -328,14 +330,30 @@ PARTITIONED BY (days(ts), category)
To write data to the sample table, your data needs to be sorted by `days(ts), category`.
-If you're inserting data with SQL statement, you can use `ORDER BY` to achieve it, like below:
+If you're inserting data with SQL statement, you can use either `ORDER BY` to trigger global sort, or `SORT BY` to trigger local sort. Global sort like below:
```sql
INSERT INTO prod.db.sample
SELECT id, data, category, ts FROM another_table
ORDER BY ts, category
```
+Local sort like below:
+
+```sql
+INSERT INTO prod.db.sample
+SELECT id, data, category, ts FROM another_table
+SORT BY ts, category
+```
+
+Of course, you can also use `SORT BY` with partition transforms.
+
+```sql
+INSERT INTO prod.db.sample
+SELECT id, data, category, ts FROM another_table
+SORT BY days(ts), category
Review comment:
I perfected the description, what do you think of this description?
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[GitHub] [iceberg] samredai commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
samredai commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r840586274
##########
File path: docs/spark/spark-writes.md
##########
@@ -311,7 +311,9 @@ distribution & sort order to Spark.
{{< /hint >}}
{{< hint info >}}
-Both global sort (`orderBy`/`sort`) and local sort (`sortWithinPartitions`) work for the requirement.
+To write with SQL, both global sort (`ORDER BY`) and local sort (`SORT BY`) work for the requirement.
Review comment:
```suggestion
With SQL, you can use `ORDER BY` to achieve global sorting or `SORT BY` to achieve local sorting.
```
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[GitHub] [iceberg] samredai commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
samredai commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r840586422
##########
File path: docs/spark/spark-writes.md
##########
@@ -311,7 +311,9 @@ distribution & sort order to Spark.
{{< /hint >}}
{{< hint info >}}
-Both global sort (`orderBy`/`sort`) and local sort (`sortWithinPartitions`) work for the requirement.
+To write with SQL, both global sort (`ORDER BY`) and local sort (`SORT BY`) work for the requirement.
+
+To write with DataFrame, both global sort (`orderBy`/`sort`) and local sort (`sortWithinPartitions`) work for the requirement.
Review comment:
```suggestion
With dataframes, you can use `orderBy`/`sort` to achieve global sorting or `sortWithinPartitions` to achieve local sorting.
```
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[GitHub] [iceberg] samredai commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
samredai commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r840582804
##########
File path: docs/spark/spark-writes.md
##########
@@ -328,14 +330,30 @@ PARTITIONED BY (days(ts), category)
To write data to the sample table, your data needs to be sorted by `days(ts), category`.
-If you're inserting data with SQL statement, you can use `ORDER BY` to achieve it, like below:
+If you're inserting data with SQL statement, you can use either `ORDER BY` to trigger global sort, or `SORT BY` to trigger local sort. Global sort like below:
Review comment:
```suggestion
In SQL, `ORDER BY` triggers a global sort and `SORT BY` triggers a local sort.
```
Then I would just show the two examples below without an introductory line "Global sort like below:" and "Local sort like below:". It should be intuitive that the examples are related to the sentence above.
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[GitHub] [iceberg] openinx commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
openinx commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r841027939
##########
File path: docs/spark/spark-writes.md
##########
@@ -328,14 +330,30 @@ PARTITIONED BY (days(ts), category)
To write data to the sample table, your data needs to be sorted by `days(ts), category`.
-If you're inserting data with SQL statement, you can use `ORDER BY` to achieve it, like below:
+If you're inserting data with SQL statement, you can use either `ORDER BY` to trigger global sort, or `SORT BY` to trigger local sort. Global sort like below:
```sql
INSERT INTO prod.db.sample
SELECT id, data, category, ts FROM another_table
ORDER BY ts, category
```
+Local sort like below:
+
+```sql
+INSERT INTO prod.db.sample
+SELECT id, data, category, ts FROM another_table
+SORT BY ts, category
+```
+
+Of course, you can also use `SORT BY` with partition transforms.
+
+```sql
+INSERT INTO prod.db.sample
+SELECT id, data, category, ts FROM another_table
+SORT BY days(ts), category
Review comment:
Should we register the `days(..)` UDF into spark environment firstly before we call it ? I will suggest to add the SQL about how to register the `days(..)` UDF.
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[GitHub] [iceberg] samredai commented on pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
samredai commented on pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#issuecomment-1085902885
Thanks for adding this @polaris6 ! I left a couple of suggestions, let me know what you think 👍
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[GitHub] [iceberg] polaris6 commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
polaris6 commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r841054093
##########
File path: docs/spark/spark-writes.md
##########
@@ -311,7 +311,9 @@ distribution & sort order to Spark.
{{< /hint >}}
{{< hint info >}}
-Both global sort (`orderBy`/`sort`) and local sort (`sortWithinPartitions`) work for the requirement.
+With SQL, you can use `ORDER BY` to achieve global sorting or `SORT BY` to achieve local sorting.
Review comment:
Of course, I updated the commit, please help to review it again, thanks!
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[GitHub] [iceberg] polaris6 commented on pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
polaris6 commented on pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#issuecomment-1085610843
cc @samredai @jackye1995
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[GitHub] [iceberg] polaris6 commented on pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
polaris6 commented on pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#issuecomment-1086566539
@openinx There is another pr here, please help me to review it, thanks!
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[GitHub] [iceberg] polaris6 commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
polaris6 commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r840617756
##########
File path: docs/spark/spark-writes.md
##########
@@ -311,7 +311,9 @@ distribution & sort order to Spark.
{{< /hint >}}
{{< hint info >}}
-Both global sort (`orderBy`/`sort`) and local sort (`sortWithinPartitions`) work for the requirement.
+To write with SQL, both global sort (`ORDER BY`) and local sort (`SORT BY`) work for the requirement.
Review comment:
yes i think so too. The revised sentence is better.
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[GitHub] [iceberg] samredai commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
samredai commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r840582804
##########
File path: docs/spark/spark-writes.md
##########
@@ -328,14 +330,30 @@ PARTITIONED BY (days(ts), category)
To write data to the sample table, your data needs to be sorted by `days(ts), category`.
-If you're inserting data with SQL statement, you can use `ORDER BY` to achieve it, like below:
+If you're inserting data with SQL statement, you can use either `ORDER BY` to trigger global sort, or `SORT BY` to trigger local sort. Global sort like below:
Review comment:
```suggestion
In SQL, `ORDER BY` triggers a global sort and `SORT BY` triggers a local sort. Here's an example of a global sort.
```
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[GitHub] [iceberg] samredai commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
samredai commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r840586977
##########
File path: docs/spark/spark-writes.md
##########
@@ -311,7 +311,9 @@ distribution & sort order to Spark.
{{< /hint >}}
{{< hint info >}}
-Both global sort (`orderBy`/`sort`) and local sort (`sortWithinPartitions`) work for the requirement.
+To write with SQL, both global sort (`ORDER BY`) and local sort (`SORT BY`) work for the requirement.
Review comment:
"the requirement" was always a bit confusing to me here. What do you think about my suggestions in this section?
##########
File path: docs/spark/spark-writes.md
##########
@@ -311,7 +311,9 @@ distribution & sort order to Spark.
{{< /hint >}}
{{< hint info >}}
-Both global sort (`orderBy`/`sort`) and local sort (`sortWithinPartitions`) work for the requirement.
+To write with SQL, both global sort (`ORDER BY`) and local sort (`SORT BY`) work for the requirement.
Review comment:
"the requirement" was always a bit confusing to me here. What do you think about this re-wording?
> With SQL, you can use `ORDER BY` to achieve global sorting or `SORT BY` to achieve local sorting.
>
> With dataframes, you can use `orderBy`/`sort` to achieve global sorting or `sortWithinPartitions` to achieve local sorting.
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[GitHub] [iceberg] samredai commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
samredai commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r840582804
##########
File path: docs/spark/spark-writes.md
##########
@@ -328,14 +330,30 @@ PARTITIONED BY (days(ts), category)
To write data to the sample table, your data needs to be sorted by `days(ts), category`.
-If you're inserting data with SQL statement, you can use `ORDER BY` to achieve it, like below:
+If you're inserting data with SQL statement, you can use either `ORDER BY` to trigger global sort, or `SORT BY` to trigger local sort. Global sort like below:
Review comment:
```suggestion
In SQL, `ORDER BY` triggers a global sort and `SORT BY` triggers a local sort.
```
Then I would just show the two examples below without an introductory line "Global sort like below:". It should be intuitive that the examples are related to the sentence above.
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[GitHub] [iceberg] polaris6 edited a comment on pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
polaris6 edited a comment on pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#issuecomment-1086566539
@openinx Hi, openinx, there is another pr here, please help me to review it, thanks!
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[GitHub] [iceberg] samredai commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
samredai commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r840584611
##########
File path: docs/spark/spark-writes.md
##########
@@ -328,14 +330,30 @@ PARTITIONED BY (days(ts), category)
To write data to the sample table, your data needs to be sorted by `days(ts), category`.
-If you're inserting data with SQL statement, you can use `ORDER BY` to achieve it, like below:
+If you're inserting data with SQL statement, you can use either `ORDER BY` to trigger global sort, or `SORT BY` to trigger local sort. Global sort like below:
```sql
INSERT INTO prod.db.sample
SELECT id, data, category, ts FROM another_table
ORDER BY ts, category
```
+Local sort like below:
+
+```sql
+INSERT INTO prod.db.sample
+SELECT id, data, category, ts FROM another_table
+SORT BY ts, category
+```
+
+Of course, you can use `SORT BY` with partition transforms:
Review comment:
```suggestion
Of course, you can also use `SORT BY` with partition transforms.
```
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[GitHub] [iceberg] samredai commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
samredai commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r840580002
##########
File path: docs/spark/spark-writes.md
##########
@@ -311,7 +311,9 @@ distribution & sort order to Spark.
{{< /hint >}}
{{< hint info >}}
-Both global sort (`orderBy`/`sort`) and local sort (`sortWithinPartitions`) work for the requirement.
+To write with SQL, both global sort (`ORDER BY`) and local sort (`SORT BY`) work for the requirement.
Review comment:
"the requirement" was always a bit confusing to me here. What do you think about this re-wording?
> With SQL, you can use `ORDER BY` to achieve global sorting or `SORT BY` to achieve local sorting.
>
> With dataframes, you can use `orderBy`/`sort` to achieve global sorting or `sortWithinPartitions` to achieve local sorting.
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[GitHub] [iceberg] polaris6 commented on a change in pull request #4463: Docs: update Spark Write doc for partitioned tables
Posted by GitBox <gi...@apache.org>.
polaris6 commented on a change in pull request #4463:
URL: https://github.com/apache/iceberg/pull/4463#discussion_r840604240
##########
File path: docs/spark/spark-writes.md
##########
@@ -328,14 +330,30 @@ PARTITIONED BY (days(ts), category)
To write data to the sample table, your data needs to be sorted by `days(ts), category`.
-If you're inserting data with SQL statement, you can use `ORDER BY` to achieve it, like below:
+If you're inserting data with SQL statement, you can use either `ORDER BY` to trigger global sort, or `SORT BY` to trigger local sort. Global sort like below:
Review comment:
The original statement is maintained here, mainly to be consistent with the description of the DataFrame.
<img width="927" alt="image" src="https://user-images.githubusercontent.com/29967142/161276564-9defd0a6-597c-4df2-ad19-78e0e2226fdc.png">
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