Import data from MaxCompute in HoloWeb
Import MaxCompute table data into Hologres as an internal table using HoloWeb's one-click synchronization. This approach delivers better query performance than creating a foreign table to query MaxCompute data directly.
Prerequisites
Before you begin, ensure that you have:
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Logged on to a Hologres instance. See Log on to an instance.
Import MaxCompute data
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Log on to the Hologres Management Console.
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In the left navigation pane at the top of the page, select the target region.
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Click Go to HoloWeb to open the HoloWeb development page.
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In the top menu bar, choose Metadata Management > MaxCompute Query Acceleration, then click Import MaxCompute Data.
Alternatively, choose Data Solutions > Import MaxCompute Data, then click Create MaxCompute Data Import Task.
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On the Create MaxCompute Data Import Task page, configure the parameters. See Parameter reference for details. SQL Script automatically parses the SQL statement for the current visual operation.
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Click Submit in the upper-right corner.
Parameter reference
Select instance
| Parameter | Description |
|---|---|
| Instance name | The name of the logged-on instance. |
MaxCompute source table
| Parameter | Description |
|---|---|
| Project name | The name of the MaxCompute project. |
| Schema name | The schema in the MaxCompute project. For projects using a two-layer model, this field is hidden. For projects using a three-layer model, select an authorized schema from the drop-down list. |
| Table name | The name of the MaxCompute table. Supports prefix-based fuzzy search. |
Hologres target table
| Parameter | Description |
|---|---|
| Database name | The Hologres database where the internal table will be created. |
| Schema name | The schema in Hologres. Defaults to public. Select another authorized schema if needed. |
| Table name | The name of the new Hologres internal table. Auto-populated from the MaxCompute table name. Rename it manually if needed. |
| Target table description | An optional description for the new internal table. |
Parameter settings
| Parameter | Description |
|---|---|
| GUC parameters | Enter the GUC parameters to configure. See GUC parameters. |
Import settings
| Parameter | Description |
|---|---|
| Fields | The MaxCompute table fields to import. Select all fields or a subset. |
Partition configuration
| Parameter | Description |
|---|---|
| Partition field | Select a partition field. Hologres creates the table as a partitioned table by default. Hologres supports only first-level partitions. If the MaxCompute table has multi-level partitions, configure only the first-level partition — the remaining levels are mapped to regular columns automatically. |
| Data timestamp | If the MaxCompute table is date-partitioned, select the partition date to import. Only data for the specified date is imported. |
Index configuration
| Parameter | Description |
|---|---|
| Storage mode | The storage layout for the internal table. Column-oriented Storage (default) suits complex analytical queries. Row-oriented Storage suits point queries and primary-key scans. Row-column Storage supports all row-store and column-store scenarios, including non-primary-key point queries. |
| Table data lifecycle | How long data is retained. Defaults to Permanent. After the lifecycle expires, rows that have not been modified within the retention period are deleted. |
| Binlog | Whether to enable Binlog. See Subscribe to Hologres Binlog. |
| Binlog lifecycle | The time-to-live (TTL) for Binlog data. Defaults to 30 days (2,592,000 seconds). |
| Distribution columns | Hologres routes rows to shards based on these columns — rows with identical values go to the same shard. Filtering on distribution columns reduces data scanned and improves query performance. |
| Segment columns | Columns used as segment keys. Queries that filter on segment columns can locate the storage position of matching rows without a full scan. |
| Clustering columns | Columns used as clustering keys. Data is physically ordered by these columns, which accelerates range queries and filter queries on the indexed columns. |
| Dictionary encoding columns | Columns for which Hologres builds a dictionary that maps string values to numeric codes. Dictionary encoding speeds up GROUP BY and filter operations on string columns. Defaults to all text columns. |
| Bitmap columns | Columns for which Hologres builds a bitmap index. Bitmap indexes can quickly filter data within fields based on specified conditions. Defaults to all text columns. |