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The following commit(s) were added to refs/heads/dev by this push:
new c6185fb3c3 [Docs] Fix missing sections in Chinese docs to align with
English documentation (#13019)
c6185fb3c3 is described below
commit c6185fb3c3263f6b20fd974d653098181d4b4344
Author: Jast <[email protected]>
AuthorDate: Thu Oct 29 10:04:23 2026 +0000
[Docs] Fix missing sections in Chinese docs to align with English
documentation (#13019)
Co-authored-by: zhangshenghang <[email protected]>
---
docs/zh/architecture/api-design/catalog-table.md | 10 ++
.../architecture/api-design/sink-architecture.md | 17 ++
.../architecture/api-design/translation-layer.md | 13 ++
docs/zh/architecture/features/multi-table.md | 54 ++++++
docs/zh/connectors/sink/Prometheus.md | 98 +++++++++++
docs/zh/connectors/sink/SensorsData.md | 60 +++++++
docs/zh/connectors/sink/StarRocks.md | 181 +++++++++++++++++++++
docs/zh/connectors/source/InfluxDB.md | 64 ++++++++
docs/zh/connectors/source/Intercom.md | 10 ++
docs/zh/connectors/source/Typeform.md | 15 +-
docs/zh/introduction/concepts/config.md | 6 +-
11 files changed, 523 insertions(+), 5 deletions(-)
diff --git a/docs/zh/architecture/api-design/catalog-table.md
b/docs/zh/architecture/api-design/catalog-table.md
index 5319040e34..f0c9fb0a31 100644
--- a/docs/zh/architecture/api-design/catalog-table.md
+++ b/docs/zh/architecture/api-design/catalog-table.md
@@ -379,3 +379,13 @@ sink {
- [sink 目标端架构](sink-architecture.md)
- [模式演化](../../introduction/configuration/schema-evolution.md)
- [模式特性](../../introduction/concepts/schema-feature.md)
+
+## 11. 参考资料
+
+### 关键源码文件
+
+-
[CatalogTable.java](../../../../seatunnel-api/src/main/java/org/apache/seatunnel/api/table/catalog/CatalogTable.java)
+-
[TableSchema.java](../../../../seatunnel-api/src/main/java/org/apache/seatunnel/api/table/catalog/TableSchema.java)
+-
[Column.java](../../../../seatunnel-api/src/main/java/org/apache/seatunnel/api/table/catalog/Column.java)
+-
[SeaTunnelDataType.java](../../../../seatunnel-api/src/main/java/org/apache/seatunnel/api/table/type/SeaTunnelDataType.java)
+-
[SchemaChangeEvent.java](../../../../seatunnel-api/src/main/java/org/apache/seatunnel/api/table/schema/event/SchemaChangeEvent.java)
diff --git a/docs/zh/architecture/api-design/sink-architecture.md
b/docs/zh/architecture/api-design/sink-architecture.md
index b879609d77..2474e72a85 100644
--- a/docs/zh/architecture/api-design/sink-architecture.md
+++ b/docs/zh/architecture/api-design/sink-architecture.md
@@ -154,6 +154,10 @@ sequenceDiagram
Note over Committer: commit 失败由框架重试\n必须保证幂等
```
+## 3. 关键实现
+
+### 3.1 SinkWriter 接口
+
**核心职责**：
- `write(element)`：接收上游记录并写入外部系统的“临时/事务内”区域（避免对外可见）
- `prepareCommit(checkpointId)`：在 checkpoint
边界生成提交信息（commitInfo），要求“无副作用”（不让数据对外可见）
@@ -209,6 +213,19 @@ sequenceDiagram
- `combine`： Sink 总所有 writer 产生的文件/分区元数据，形成一次表级提交所需的“全量变更集”
- `commit`：对外部 metastore/表事务执行一次全局原子提交；失败后需要可重试且不重复（幂等）
+### 3.4 代码参考
+
+**API 接口**：
+-
[SeaTunnelSink.java](../../../../seatunnel-api/src/main/java/org/apache/seatunnel/api/sink/SeaTunnelSink.java)
+-
[SinkWriter.java](../../../../seatunnel-api/src/main/java/org/apache/seatunnel/api/sink/SinkWriter.java)
+-
[SinkCommitter.java](../../../../seatunnel-api/src/main/java/org/apache/seatunnel/api/sink/SinkCommitter.java)
+-
[SinkAggregatedCommitter.java](../../../../seatunnel-api/src/main/java/org/apache/seatunnel/api/sink/SinkAggregatedCommitter.java)
+
+**示例实现**：
+- JDBC
Sink：`seatunnel-connectors-v2/connector-jdbc/src/main/java/org/apache/seatunnel/connectors/seatunnel/jdbc/sink/`
+- Kafka
Sink：`seatunnel-connectors-v2/connector-kafka/src/main/java/org/apache/seatunnel/connectors/seatunnel/kafka/sink/`
+- File
Sink：`seatunnel-connectors-v2/connector-file/connector-file-base/src/main/java/org/apache/seatunnel/connectors/seatunnel/file/sink/`
+
## 4. 设计考量
### 4.1 设计权衡
diff --git a/docs/zh/architecture/api-design/translation-layer.md
b/docs/zh/architecture/api-design/translation-layer.md
index 7db68c39b6..db11a265d7 100644
--- a/docs/zh/architecture/api-design/translation-layer.md
+++ b/docs/zh/architecture/api-design/translation-layer.md
@@ -254,3 +254,16 @@ SeaTunnel 侧使用统一抽象类型；转换层根据引擎能力与用户配
- [数据 Source 架构](../api-design/source-architecture.md)
- [目标端 Sink 架构](../api-design/sink-architecture.md)
- [设计理念](../design-philosophy.md)
+
+## 10. 参考资料
+
+### 关键源码文件
+
+- Flink 转换层：`seatunnel-translation/seatunnel-translation-flink/`
+- Spark 转换层：`seatunnel-translation/seatunnel-translation-spark/`
+- 基础接口：`seatunnel-api/src/main/java/org/apache/seatunnel/api/`
+
+### 延伸阅读
+
+- [Apache Flink Source
API](https://nightlies.apache.org/flink/flink-docs-stable/docs/dev/datastream/sources/)
+- [Apache Spark Data Source
V2](https://spark.apache.org/docs/latest/sql-data-sources.html)
diff --git a/docs/zh/architecture/features/multi-table.md
b/docs/zh/architecture/features/multi-table.md
index 30bdce1313..c0bb7ca407 100644
--- a/docs/zh/architecture/features/multi-table.md
+++ b/docs/zh/architecture/features/multi-table.md
@@ -453,6 +453,60 @@ env {
该配置不处理共享故障，例如 source 连接中断、checkpoint 协调失败、插件加载失败或 OOM；这类异常仍会导致整个作业失败。
+## 11. 限制与注意事项
+
+### 11.1 当前限制
+
+**并行度共享**：
+- 所有表共享同一并行度
+- 无法为每张表单独设置并行度
+
+**副本数固定**：
+- 所有表使用相同的副本数
+- 高吞吐表和低吞吐表被同等对待
+
+**内存开销**：
+- 每个写入器维护独立的缓冲区
+- 100 张表 × 4 个副本 = 内存中 400 个写入器
+
+### 11.2 应对方法
+
+**高吞吐表**：
+```hocon
+# 方案一：为热点表拆分独立作业
+job-1 { source { table-name = "orders" } } # 独立作业
+
+job-2 { source { table-name = "user_.*|product_.*" } } # 其余表
+```
+
+**内存优化**：
+```hocon
+# 减小每个写入器的缓冲区
+sink {
+ JDBC {
+ batch-size = 500 # 更小的批次
+ }
+}
+```
+
+## 12. 后续增强
+
+### 12.1 动态副本
+
+当前的 `multi_table_sink_replica` 参数不支持按表覆盖副本数（它对所有表生效）。如果需要按表设置副本数，
+还需要额外的 connector/框架能力支持。
+
+### 12.2 自适应副本
+
+```java
+// 根据吞吐量自动调整副本数
+if (table.getWriteRate() > threshold) {
+ increaseReplicas(table);
+} else if (table.getWriteRate() < lowThreshold) {
+ decreaseReplicas(table);
+}
+```
+
## 13. 相关资源
- [CatalogTable 和元数据](../api-design/catalog-table.md)
diff --git a/docs/zh/connectors/sink/Prometheus.md
b/docs/zh/connectors/sink/Prometheus.md
index b57be92e0d..10e1efe70e 100644
--- a/docs/zh/connectors/sink/Prometheus.md
+++ b/docs/zh/connectors/sink/Prometheus.md
@@ -157,6 +157,104 @@ sink {
}
```
+## 流式 Remote Write 与批量刷新
+
+下面的示例以流式模式从 Kafka 读取数据并写入 Prometheus remote write 端点。Sink 会先缓冲最多
+`batch_size` 行数据再发起 HTTP 写入，同时引擎级的 `sink.flush.interval`（仅 Zeta 支持）每 10 秒
+强制刷新一次缓冲区，即使上游数据流处于空闲状态，指标样本也会持续发送。
+
+```hocon
+env {
+ parallelism = 2
+ job.mode = "STREAMING"
+ checkpoint.interval = 30000
+ sink.flush.interval = 10000
+}
+
+source {
+ Kafka {
+ plugin_output = "metrics_topic"
+ bootstrap.servers = "kafka:9092"
+ topic = "metrics"
+ format = "json"
+ schema = {
+ fields {
+ c_map = "map<string, string>"
+ c_double = double
+ c_timestamp = bigint
+ }
+ }
+ }
+}
+
+sink {
+ Prometheus {
+ plugin_input = "metrics_topic"
+ url = "http://prometheus:9090/api/v1/write";
+ key_label = "c_map"
+ key_value = "c_double"
+ key_timestamp = "c_timestamp"
+ batch_size = 2048
+ retry = 5
+ retry_backoff_multiplier_ms = 200
+ retry_backoff_max_ms = 10000
+ }
+}
+```
+
+## 多表 Remote Write
+
+当同一个作业从多张上游表读取数据并写入同一个 Prometheus remote write 端点时，可以通过
+`multi_table_sink_replica` 控制每张表分配多少个写入任务。表都比较小时使用默认值 `1` 即可；
+只有当某张表需要比其他表更高的并行度时才需要调大该值。
+
+```hocon
+env {
+ parallelism = 2
+ job.mode = "BATCH"
+}
+
+source {
+ FakeSource {
+ plugin_output = "fake_app_a"
+ schema = {
+ fields {
+ c_map = "map<string, string>"
+ c_double = double
+ c_timestamp = timestamp
+ }
+ }
+ rows = [
+ { kind = INSERT, fields = [{"__name__" : "app_a_metric"}, 1.0,
CURRENT_TIMESTAMP] }
+ ]
+ }
+ FakeSource {
+ plugin_output = "fake_app_b"
+ schema = {
+ fields {
+ c_map = "map<string, string>"
+ c_double = double
+ c_timestamp = timestamp
+ }
+ }
+ rows = [
+ { kind = INSERT, fields = [{"__name__" : "app_b_metric"}, 2.0,
CURRENT_TIMESTAMP] }
+ ]
+ }
+}
+
+sink {
+ Prometheus {
+ plugin_input = ["fake_app_a", "fake_app_b"]
+ url = "http://prometheus:9090/api/v1/write";
+ key_label = "c_map"
+ key_value = "c_double"
+ key_timestamp = "c_timestamp"
+ multi_table_sink_replica = 2
+ }
+}
+```
+
## 变更日志
<ChangeLog />
diff --git a/docs/zh/connectors/sink/SensorsData.md
b/docs/zh/connectors/sink/SensorsData.md
index ad2e035880..113503a4d9 100644
--- a/docs/zh/connectors/sink/SensorsData.md
+++ b/docs/zh/connectors/sink/SensorsData.md
@@ -278,6 +278,66 @@ sink {
}
```
+### 用户明细（Detail 记录）
+
+用户明细记录（`record_type = "details"`）会为 SensorsData 用户附加一条按记录维度的标识。
+`detail_id_column` 提供明细键，`distinct_id_column` 和 `identity_fields` 用于标识所属用户。
+
+```hocon
+sink {
+ SensorsData {
+ consumer = console
+ server_url = "http://10.129.27.43:8106/sa?project=sditest";
+ time_free = true
+
+ record_type = details
+ schema = fund_manager
+ distinct_id_column = c_id
+ detail_id_column = c_id
+ identity_fields = [
+ { target = "$identity_distinct_id", source = c_id }
+ ]
+ property_fields = [
+ { target = c_id, source = c_id, type = STRING }
+ { target = fund_amount, source = c_int, type = INT }
+ { target = "$is_valid", source = c_boolean, type = BOOLEAN }
+ ]
+ }
+}
+```
+
+### 多身份与动态事件名称
+
+下面的示例直接从数据行本身构造事件名称（`event_name = "${c_event}"`），并一次性映射多个身份
+（`$identity_login_id`、`$identity_distinct_id`）。转换失败的记录会通过 `skip_error_record =
true` 跳过。
+
+```hocon
+sink {
+ SensorsData {
+ consumer = console
+ server_url = "http://10.1.136.63:8106/sa?project=default";
+ time_free = true
+
+ record_type = events
+ schema = events
+ event_name = "${c_event}"
+ time_column = c_date
+ distinct_id_column = c_bigint
+ identity_fields = [
+ { source = c_bigint, target = "$identity_login_id" }
+ { source = c_bigint, target = "$identity_distinct_id" }
+ ]
+ property_fields = [
+ { target = c_tinyint, source = c_tinyint, type = INT }
+ { target = c_bigint, source = c_bigint, type = BIGINT }
+ { target = c_int, source = c_int, type = INT }
+ { target = c_boolean, source = c_boolean, type = BOOLEAN }
+ ]
+ skip_error_record = true
+ }
+}
+```
+
### 控制台输出（用于测试）
```hocon
diff --git a/docs/zh/connectors/sink/StarRocks.md
b/docs/zh/connectors/sink/StarRocks.md
index 24e1e36b2e..ae0303daa9 100644
--- a/docs/zh/connectors/sink/StarRocks.md
+++ b/docs/zh/connectors/sink/StarRocks.md
@@ -377,6 +377,187 @@ sink {
}
```
+### CDC 与 Schema 变更
+
+下面的示例演示 MySQL-CDC 以 `schema-changes.enabled = true` 的方式写入 StarRocks，这样上游 MySQL
的 DDL 变更
+（新增列、类型加宽等）会同步应用到目标 StarRocks 主键表上。
+
+```hocon
+env {
+ job.mode = "STREAMING"
+ checkpoint.interval = 2000
+}
+
+source {
+ MySQL-CDC {
+ username = "st_user_source"
+ password = "mysqlpw"
+ table-names = ["shop.products", "shop.orders", "shop.customers"]
+ url = "jdbc:mysql://mysql_cdc_e2e:3306/shop"
+
+ schema-changes.enabled = true
+ }
+}
+
+sink {
+ StarRocks {
+ nodeUrls = ["starrocks_cdc_e2e:8040"]
+ base-url = "jdbc:mysql://starrocks_cdc_e2e:9030/shop"
+ username = "root"
+ password = ""
+ database = "shop"
+ table = "${table_name}"
+ max_retries = 3
+ enable_upsert_delete = true
+ schema_save_mode = "RECREATE_SCHEMA"
+ data_save_mode = "DROP_DATA"
+ save_mode_create_template = """
+ CREATE TABLE IF NOT EXISTS shop.`${table_name}` (
+ ${rowtype_primary_key},
+ ${rowtype_fields}
+ ) ENGINE=OLAP
+ PRIMARY KEY (${rowtype_primary_key})
+ DISTRIBUTED BY HASH (${rowtype_primary_key})
+ PROPERTIES (
+ "replication_num" = "1",
+ "in_memory" = "false",
+ "enable_persistent_index" = "true",
+ "replicated_storage" = "true",
+ "compression" = "LZ4"
+ )
+ """
+ }
+}
+```
+
+### MySQL-CDC 与定时刷新
+
+下面的示例在流式作业中配置了 `sink.flush.interval`，使 StarRocks Sink 每隔 500 ms 刷新一次缓冲区，
+不再受 `batch_max_rows` 和 `batch_max_bytes` 的限制。
+
+```hocon
+env {
+ parallelism = 1
+ job.mode = "STREAMING"
+ checkpoint.interval = 300000
+ sink.flush.interval = 500
+}
+
+source {
+ MySQL-CDC {
+ server-id = 5670
+ username = "st_user_source"
+ password = "mysqlpw"
+ table-names = ["shop.products"]
+ url = "jdbc:mysql://mysql_starrocks_timer_flush_e2e:3306/shop"
+ }
+}
+
+sink {
+ StarRocks {
+ nodeUrls = ["starrocks_timer_flush_e2e:8030"]
+ base-url = "jdbc:mysql://starrocks_timer_flush_e2e:9030/timer_flush"
+ username = root
+ password = ""
+ database = "timer_flush"
+ table = "starrocks_timer_flush"
+ labelPrefix = "timer-flush-"
+ batch_max_rows = 100000
+ batch_max_bytes = 104857600
+ schema_save_mode = "IGNORE"
+ data_save_mode = "APPEND_DATA"
+ starrocks.config = {
+ format = "JSON"
+ }
+ }
+}
+```
+
+### 多表
+
+#### 示例1
+
+```hocon
+env {
+ parallelism = 1
+ job.mode = "STREAMING"
+ checkpoint.interval = 5000
+}
+
+source {
+ Mysql-CDC {
+ base-url = "jdbc:mysql://127.0.0.1:3306/seatunnel"
+ username = "root"
+ password = "******"
+
+ table-names = ["seatunnel.role","seatunnel.user","galileo.Bucket"]
+ }
+}
+
+transform {
+}
+
+sink {
+ StarRocks {
+ nodeUrls = ["e2e_starRocksdb:8030"]
+ base-url = "jdbc:mysql://e2e_starRocksdb:9030/"
+ username = root
+ password = ""
+ database = "${database_name}_test"
+ table = "${table_name}_test"
+ ...
+
+ // 支持 upsert/delete 事件同步（enable_upsert_delete=true），仅支持 PrimaryKey 模型。
+ enable_upsert_delete = true
+ }
+}
+```
+
+#### 示例2
+
+```hocon
+env {
+ parallelism = 1
+ job.mode = "BATCH"
+}
+
+source {
+ Jdbc {
+ driver = oracle.jdbc.driver.OracleDriver
+ url = "jdbc:oracle:thin:@localhost:1521/XE"
+ user = testUser
+ password = testPassword
+
+ table_list = [
+ {
+ table_path = "TESTSCHEMA.TABLE_1"
+ },
+ {
+ table_path = "TESTSCHEMA.TABLE_2"
+ }
+ ]
+ }
+}
+
+transform {
+}
+
+sink {
+ StarRocks {
+ nodeUrls = ["e2e_starRocksdb:8030"]
+ base-url = "jdbc:mysql://e2e_starRocksdb:9030/"
+ username = root
+ password = ""
+ database = "${schema_name}_test"
+ table = "${table_name}_test"
+ ...
+
+ // 支持 upsert/delete 事件同步（enable_upsert_delete=true），仅支持 PrimaryKey 模型。
+ enable_upsert_delete = true
+ }
+}
+```
+
## 常见问题
### StarRocks Sink 支持自动建表吗？
diff --git a/docs/zh/connectors/source/InfluxDB.md
b/docs/zh/connectors/source/InfluxDB.md
index b4f35f3568..0f78b41273 100644
--- a/docs/zh/connectors/source/InfluxDB.md
+++ b/docs/zh/connectors/source/InfluxDB.md
@@ -159,6 +159,19 @@ split 2: select * from test where ($split_column >= 6 and
$split_column < 11) an
> 提示：确保 `upper_bound - lower_bound` 能被 `partition_num` 整除，否则查询结果会重叠。
+### where [string]
+
+:::caution 保留参数
+
+当前的切分逻辑会直接从 `sql` 参数中读取小写的 `where` 关键字。设置 `where` 参数对生成的切分查询
+没有任何效果——请把过滤条件直接写进 `sql` 中，例如 `select * from test where age > 0`。切分解析器
+对 `where` 关键字区分大小写。
+
+该参数保留在参数列表中，只是因为校验规则（`InfluxDBSourceFactory.optionRule()`）为了向后兼容仍然
+引用了它；运行时的切分查询生成器不会读取该参数。
+
+:::
+
### epoch [string]
InfluxDB 返回的时间精度。可选值：`H`、`m`、`s`、`MS`、`u`、`n`，默认值为 `n`。
@@ -319,6 +332,57 @@ sink {
}
```
+### 有界读取与并行切分
+
+InfluxDB Source 的读取范围由 `sql` 的结果决定。如果需要把它接入流式 Sink 且不丢数据，可以设置一个
+有限的 `partition_num`，让 SeaTunnel 通过检查点记录每个切分的读取位置。
+
+```hocon
+env {
+ parallelism = 2
+ job.mode = "BATCH"
+ checkpoint.interval = 10000
+}
+
+source {
+ InfluxDB {
+ url = "http://influxdb-host:8086";
+ sql = "select label, c_string, c_double, c_bigint, c_float, c_int,
c_smallint, c_boolean from source"
+ database = "test"
+ lower_bound = 0
+ upper_bound = 99
+ partition_num = 4
+ split_column = "c_int"
+ query_timeout_sec = 10
+ connect_timeout_ms = 20000
+ schema {
+ fields {
+ label = STRING
+ c_string = STRING
+ c_double = DOUBLE
+ c_bigint = BIGINT
+ c_float = FLOAT
+ c_int = INT
+ c_smallint = SMALLINT
+ c_boolean = BOOLEAN
+ time = BIGINT
+ }
+ }
+ }
+}
+
+sink {
+ InfluxDB {
+ url = "http://influxdb-host:8086";
+ database = "test"
+ measurement = "sink"
+ key_time = "time"
+ key_tags = ["label"]
+ batch_size = 1024
+ }
+}
+```
+
## 变更日志
<ChangeLog />
diff --git a/docs/zh/connectors/source/Intercom.md
b/docs/zh/connectors/source/Intercom.md
index 8bbd122aac..3e4bbc53be 100644
--- a/docs/zh/connectors/source/Intercom.md
+++ b/docs/zh/connectors/source/Intercom.md
@@ -29,6 +29,16 @@ import ChangeLog from
'../changelog/connector-http-intercom.md';
| retry_backoff_multiplier_ms | Int | 否 | `100` | 退避倍数（毫秒）。 |
| retry_backoff_max_ms | Int | 否 | `10000` | 最大退避时间（毫秒）。 |
+### api_key
+只会通过 `Authorization: Bearer <token>` 请求头发送。连接器不会在日志中输出请求头或配置，也不会
+持久化任何状态，因此该令牌不会进入检查点。引擎在打印作业配置时是否对 `api_key` 做脱敏处理，
+不在本连接器的控制范围内。
+
+### retry
+HTTP 429 和 5xx 的最大重试次数（基础 HTTP 客户端中还包括 IOException）。退避时间从
+`retry_backoff_multiplier_ms` 开始翻倍，直到 `retry_backoff_max_ms`。不会遵循
`Retry-After` 响应头。
+Intercom 的默认限流为每个应用每分钟 10,000 次调用（每个工作区 25,000 次），按 10 秒窗口执行限制。
+
## 输出列
`id`、`role`、`email`、`name`、`phone`、`external_id`（均为 STRING，后三者可为 null），
diff --git a/docs/zh/connectors/source/Typeform.md
b/docs/zh/connectors/source/Typeform.md
index 0d060b5d65..bc6afcf6f6 100644
--- a/docs/zh/connectors/source/Typeform.md
+++ b/docs/zh/connectors/source/Typeform.md
@@ -33,8 +33,19 @@ import ChangeLog from
'../changelog/connector-http-typeform.md';
| retry_backoff_multiplier_ms | Int | 否 | `100` | 退避倍数（毫秒）。 |
| retry_backoff_max_ms | Int | 否 | `10000` | 最大退避时间（毫秒）。 |
-令牌只放在 `Authorization: Bearer <token>` 请求头中，不会出现在查询参数、日志或作业状态里。
-Typeform 每个账号每秒允许 2 个请求，因此连接器会让请求间隔至少 500 毫秒。
+### api_key
+只会通过 `Authorization: Bearer <token>` 请求头发送，绝不会出现在查询参数中。连接器不会在日志中
+输出请求头或配置，也不会持久化任何状态，因此该令牌不会进入检查点。引擎在打印作业配置时是否对
+`api_key` 做脱敏处理，不在本连接器的控制范围内。
+
+### since / until / response_type
+这三个参数会原样传给 Typeform。对于已完成的回复，Typeform 按 `submitted_at` 过滤 `since` 和 `until`；
+对于其他回复类型则使用不同的时间戳（参见 Typeform 的 API 参考）。
+
+### retry
+请求之间的间隔至少 500 毫秒，因为 Typeform 每个账号每秒只允许 2 个请求。HTTP 429 和 5xx 会进行重试，
+退避时间从 `retry_backoff_multiplier_ms` 开始翻倍，直到 `retry_backoff_max_ms`。不会遵循
`Retry-After`
+响应头。
## 输出列
diff --git a/docs/zh/introduction/concepts/config.md
b/docs/zh/introduction/concepts/config.md
index 52ffb947f3..6befacb32f 100644
--- a/docs/zh/introduction/concepts/config.md
+++ b/docs/zh/introduction/concepts/config.md
@@ -206,7 +206,7 @@ sql = """ select * from "table" """
在配置文件中，我们可以定义一些变量并在运行时替换它们。但请注意，目前仅支持 HOCON 格式的文件。
-变量使用方法：
+### 变量使用方法：
- `${varName}`，如果变量未传值，则抛出异常。
- `${varName:default}`，如果变量未传值，则使用默认值。如果设置默认值则变量需要写在双引号中。
- `${varName:}`，如果变量未传值，则使用空字符串。
@@ -220,7 +220,7 @@ export varName="value with space"
如果您在配置文件中设置了没有默认值的变量，但在执行过程中未传递该变量，则会保留该变量值，系统不会抛出异常。但请您需要确保其他流程能够正确解析该变量值。例如，ElasticSearch的索引需要支持`${xxx}`这样的格式来动态指定索引。若其他流程不支持，程序可能无法正常运行。
-具体样例：
+### 示例：
```hocon
env {
job.mode = "BATCH"
@@ -321,7 +321,7 @@ sink {
```
-一些注意事项:
+### 注意事项:
- 为了避免非预期的数据同步错误，`-i` 传参不能出现重复的key。
- 如果值包含逗号，需要用`\"`包裹起来，如 `-i read_cols=\"id,name\"`，但list和map类型不需要用`\"`包裹，如`-i
include_fields=[id,name]`。
- 如果值包含特殊字符，如`(`，请使用`'`引号将其括起来。
