Data loading
🗃️ Loading overview
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🗃️ Load from Object Storage
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📄️ Load data from a local file system
StarRocks provides two methods of loading data from a local file system:
📄️ Load data from HDFS
StarRocks provides the following options for loading data from HDFS:
🗃️ Load data from Apache Kafka
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🗃️ Load data from Apache Spark
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📄️ Load data using INSERT
This topic describes how to load data into StarRocks by using a SQL statement - INSERT.
📄️ Load data using Stream Load transaction interface
From v2.4 onwards, StarRocks provides a Stream Load transaction interface to implement two-phase commit (2PC) for transactions that are run to load data from external systems such as Apache Flink® and Apache Kafka®. The Stream Load transaction interface helps improve the performance of highly concurrent stream loads.
📄️ Realtime synchronization from MySQL
StarRocks supports multiple methods to synchronize data from MySQL to StarRocks in real time, delivering low latency real-time analytics of massive data.
📄️ Continuously load data from Apache Flink®
StarRocks provides a self-developed connector named StarRocks Connector for Apache Flink® (Flink connector for short) to help you load data into a StarRocks table by using Flink. The basic principle is to accumulate the data and then load it all at a time into StarRocks through STREAM LOAD.
📄️ Change data through loading
Primary Key tables provided by StarRocks allow you to make data changes to StarRocks tables by running Stream Load, Broker Load, or Routine Load jobs. These data changes include inserts, updates, and deletions. However, Primary Key tables do not support changing data by using Spark Load or INSERT.
📄️ Transform data at loading
StarRocks supports data transformation at loading.
📄️ Load data using tools
StarRocks and its ecosystem partners offer the following tools to help you seamlessly integrate StarRocks with external databases.
📄️ Strict mode
Strict mode is an optional property that you can configure for data loads. It affects the loading behavior and the final loaded data.