feat: readme for example module

Author: fengjiachun

ingester-example/README.md

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+# GreptimeDB Ingester Examples
+
+## Unary Write
+
+The unary write API provides a straightforward way to write data to GreptimeDB in a single request. It returns a `CompletableFuture<Result<WriteOk, Err>>` that completes when the write operation finishes. This asynchronous design enables high-performance data ingestion while providing clear success/failure information through the Result pattern.
+
+This API is suitable for most scenarios and serves as an excellent default choice when you're unsure which API to use.
+
+### Performance Recommendations
+
+For optimal performance, we recommend batching your writes whenever possible:
+
+- **Batch multiple rows**: Sending 500 rows in a single call rather than making 500 individual calls will significantly improve throughput and reduce network overhead.
+- **Combine multiple tables**: This API allows you to write data to multiple tables in a single call, making it convenient to batch related data before sending it to the database.
+
+These batching approaches can dramatically improve performance compared to making separate calls for each row or table, especially in high-throughput scenarios.
+
+### Examples
+
+- [LowLevelApiWriteQuickStart.java](src/main/java/io/greptime/LowLevelApiWriteQuickStart.java)
+
+  This example demonstrates how to use the low-level API to write data to GreptimeDB. It covers:
+  * Defining table schemas with tags, timestamps, and fields
+  * Writing multiple rows of data to different tables
+  * Processing write results using the Result pattern
+  * Deleting data using the `WriteOp.Delete` operation
+
+- [HighLevelApiWriteQuickStart.java](src/main/java/io/greptime/HighLevelApiWriteQuickStart.java)
+
+  This example demonstrates how to use the high-level API to write data to GreptimeDB. It covers:
+  * Writing data using POJO objects with annotations
+  * Handling multiple tables in a single write operation
+  * Processing write results asynchronously
+  * Deleting data using the `WriteOp.Delete` operation
+
+## Streaming Write
+
+The streaming write API establishes a continuous connection for sending data to GreptimeDB, offering a convenient way to write data over time. This approach allows you to write data from different tables in a single stream, prioritizing ease of use over maximum performance.
+
+This API is particularly well-suited for:
+- Low-volume continuous data writing scenarios
+- Applications that need to write to multiple tables through a single connection
+- Cases where simplicity and convenience are more important than maximum throughput
+
+### Examples
+
+- [LowLevelApiStreamWriteQuickStart.java](src/main/java/io/greptime/LowLevelApiStreamWriteQuickStart.java)
+
+  This example demonstrates how to use the low-level API to write data to GreptimeDB using stream. It covers:
+  * Defining table schemas with tags, timestamps, and fields
+  * Writing multiple rows of data to different tables via streaming
+  * Finalizing the stream and retrieving write results
+  * Deleting data using the `WriteOp.Delete` operation
+
+- [HighLevelApiStreamWriteQuickStart.java](src/main/java/io/greptime/HighLevelApiStreamWriteQuickStart.java)
+
+  This example demonstrates how to use the high-level API to write data to GreptimeDB using stream. It covers:
+  * Writing POJO objects directly to the stream
+  * Managing multiple data types in a single stream
+  * Finalizing the stream and processing results
+  * Deleting data using the `WriteOp.Delete` operation
+
+## Bulk Streaming Write
+
+The bulk streaming write API is optimized specifically for high-performance, high-throughput scenarios. Unlike regular streaming, this API allows continuous writing to only one table per stream, but can handle very large data volumes (up to 200MB per write). It features sophisticated adaptive flow control mechanisms that automatically adjust to your data throughput requirements.
+
+This API is ideal for scenarios such as:
+- Massive log data ingestion requiring high throughput
+- Time-series data collection systems that need to process large volumes of data
+- Applications where performance and throughput are critical requirements
+
+### Examples
+
+- [BulkWriteApiQuickStart.java](src/main/java/io/greptime/BulkWriteApiQuickStart.java)
+
+  This example demonstrates how to use the bulk write API to write large volumes of data to a single table with maximum efficiency. It covers:
+  * Configuring the bulk writer for optimal performance
+  * Writing large batches of data to a single table
+  * Leveraging the adaptive flow control mechanisms
+  * Processing write results asynchronously