leesf commented on a change in pull request #1761:
URL: https://github.com/apache/hudi/pull/1761#discussion_r447592462
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File path: docs/_docs/2_2_writing_data.md
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@@ -176,15 +176,49 @@ In some cases, you may want to migrate your existing
table into Hudi beforehand.
## Datasource Writer
-The `hudi-spark` module offers the DataSource API to write (and also read) any
data frame into a Hudi table.
-Following is how we can upsert a dataframe, while specifying the field names
that need to be used
-for `recordKey => _row_key`, `partitionPath => partition` and `precombineKey
=> timestamp`
+The `hudi-spark` module offers the DataSource API to write (and read) a Spark
DataFrame into a Hudi table. There are a number of options available:
+**`HoodieWriteConfig`**:
+
+**TABLE_NAME** (Required)<br>
+
+
+**`DataSourceWriteOptions`**:
+
+**RECORDKEY_FIELD_OPT_KEY** (Required): Primary key field(s). Nested fields
can be specified using the dot notation eg: `a.b.c`. When using multiple
columns as primary key use comma separated notation, eg:
`"col1,col2,col3,etc"`. Single or multiple columns as primary key specified by
`KEYGENERATOR_CLASS_OPT_KEY` property.<br>
+Default value: `"uuid"`<br>
+
+**PARTITIONPATH_FIELD_OPT_KEY** (Required): Columns to be used for
partitioning the table. To prevent partitioning, provide empty string as value
eg: `""`. Specify partitioning/no partitioning using
`KEYGENERATOR_CLASS_OPT_KEY` and if using hive
`HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY`<br>
Review comment:
how about
Specify partitioning/no partitioning using `KEYGENERATOR_CLASS_OPT_KEY` and
using `HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY` when syncing to hive ?
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