|
17 | 17 | # specific language governing permissions and limitations |
18 | 18 | # under the License. |
19 | 19 | # |
20 | | -# Hide `/in-dev/` |
21 | | -toc_hide: true |
22 | | -hide_summary: true |
23 | | -exclude_search: true |
| 20 | +linkTitle: 'In Development' |
| 21 | +title: 'Overview' |
| 22 | +type: docs |
| 23 | +weight: 200 |
| 24 | +params: |
| 25 | + top_hidden: true |
| 26 | + show_page_toc: false |
| 27 | +cascade: |
| 28 | + type: docs |
| 29 | + params: |
| 30 | + show_page_toc: true |
| 31 | +# This file will NOT be copied into a new release's versioned docs folder. |
24 | 32 | --- |
| 33 | + |
| 34 | +> [!WARNING] |
| 35 | +> These pages refer to the current state of the main branch, which is still under active development. |
| 36 | +> |
| 37 | +> Functionalities can be changed, removed or added without prior notice. |
| 38 | +
|
| 39 | +Apache Polaris (Incubating) is a catalog implementation for Apache Iceberg™ tables and is built on the open source Apache Iceberg™ REST protocol. |
| 40 | + |
| 41 | +With Polaris, you can provide centralized, secure read and write access to your Iceberg tables across different REST-compatible query engines. |
| 42 | + |
| 43 | + overview") |
| 44 | + |
| 45 | +## Key concepts |
| 46 | + |
| 47 | +This section introduces key concepts associated with using Apache Polaris (Incubating). |
| 48 | + |
| 49 | +In the following diagram, a sample [Apache Polaris (Incubating) structure](#catalog) with nested [namespaces](#namespace) is shown for Catalog1. No tables |
| 50 | +or namespaces have been created yet for Catalog2 or Catalog3. |
| 51 | + |
| 52 | + structure") |
| 53 | + |
| 54 | +### Catalog |
| 55 | + |
| 56 | +In Polaris, you can create one or more catalog resources to organize Iceberg tables. |
| 57 | + |
| 58 | +Configure your catalog by setting values in the storage configuration for S3, Azure, or Google Cloud Storage. An Iceberg catalog enables a |
| 59 | +query engine to manage and organize tables. The catalog forms the first architectural layer in the [Apache Iceberg™ table specification](https://iceberg.apache.org/spec/#overview) and must support the following tasks: |
| 60 | + |
| 61 | +- Storing the current metadata pointer for one or more Iceberg tables. A metadata pointer maps a table name to the location of that table's |
| 62 | + current metadata file. |
| 63 | + |
| 64 | +- Performing atomic operations so that you can update the current metadata pointer for a table to the metadata pointer of a new version of |
| 65 | + the table. |
| 66 | + |
| 67 | +To learn more about Iceberg catalogs, see the [Apache Iceberg™ documentation](https://iceberg.apache.org/concepts/catalog/). |
| 68 | + |
| 69 | +#### Catalog types |
| 70 | + |
| 71 | +A catalog can be one of the following two types: |
| 72 | + |
| 73 | +- Internal: The catalog is managed by Polaris. Tables from this catalog can be read and written in Polaris. |
| 74 | + |
| 75 | +- External: The catalog is externally managed by another Iceberg catalog provider (for example, Snowflake, Glue, Dremio Arctic). Tables from |
| 76 | + this catalog are synced to Polaris. These tables are read-only in Polaris. |
| 77 | + |
| 78 | +A catalog is configured with a storage configuration that can point to S3, Azure storage, or GCS. |
| 79 | + |
| 80 | +### Namespace |
| 81 | + |
| 82 | +You create *namespaces* to logically group Iceberg tables within a catalog. A catalog can have multiple namespaces. You can also create |
| 83 | +nested namespaces. Iceberg tables belong to namespaces. |
| 84 | + |
| 85 | +> [!Important] |
| 86 | +> For the access privileges defined for a catalog to be enforced correctly, the following conditions must be met: |
| 87 | +> |
| 88 | +> - The directory only contains the data files that belong to a single table. |
| 89 | +> - The directory hierarchy matches the namespace hierarchy for the catalog. |
| 90 | +> |
| 91 | +> For example, if a catalog includes the following items: |
| 92 | +> |
| 93 | +> - Top-level namespace namespace1 |
| 94 | +> - Nested namespace namespace1a |
| 95 | +> - A customers table, which is grouped under nested namespace namespace1a |
| 96 | +> - An orders table, which is grouped under nested namespace namespace1a |
| 97 | +> |
| 98 | +> The directory hierarchy for the catalog must follow this structure: |
| 99 | +> |
| 100 | +> - /namespace1/namespace1a/customers/<files for the customers table *only*> |
| 101 | +> - /namespace1/namespace1a/orders/<files for the orders table *only*> |
| 102 | +
|
| 103 | +### Storage configuration |
| 104 | + |
| 105 | +A storage configuration stores a generated identity and access management (IAM) entity for your cloud storage and is created |
| 106 | +when you create a catalog. The storage configuration is used to set the values to connect Polaris to your cloud storage. During the |
| 107 | +catalog creation process, an IAM entity is generated and used to create a trust relationship between the cloud storage provider and Polaris |
| 108 | +Catalog. |
| 109 | + |
| 110 | +When you create a catalog, you supply the following information about your cloud storage: |
| 111 | + |
| 112 | +| Cloud storage provider | Information | |
| 113 | +| -----------------------| ----------- | |
| 114 | +| Amazon S3 | <ul><li>Default base location for your Amazon S3 bucket</li><li>Locations for your Amazon S3 bucket</li><li>S3 role ARN</li><li>External ID (optional)</li></ul> | |
| 115 | +| Google Cloud Storage (GCS) | <ul><li>Default base location for your GCS bucket</li><li>Locations for your GCS bucket</li></ul> | |
| 116 | +| Azure | <ul><li>Default base location for your Microsoft Azure container</li><li>Locations for your Microsoft Azure container</li><li>Azure tenant ID</li></ul> | |
| 117 | + |
| 118 | +## Example workflow |
| 119 | + |
| 120 | +In the following example workflow, Bob creates an Apache Iceberg™ table named Table1 and Alice reads data from Table1. |
| 121 | + |
| 122 | +1. Bob uses Apache Spark™ to create the Table1 table under the |
| 123 | + Namespace1 namespace in the Catalog1 catalog and insert values into |
| 124 | + Table1. |
| 125 | + |
| 126 | + Bob can create Table1 and insert data into it because he is using a |
| 127 | + service connection with a service principal that has |
| 128 | + the privileges to perform these actions. |
| 129 | + |
| 130 | +2. Alice uses Snowflake to read data from Table1. |
| 131 | + |
| 132 | + Alice can read data from Table1 because she is using a service |
| 133 | + connection with a service principal with a catalog integration that |
| 134 | + has the privileges to perform this action. Alice |
| 135 | + creates an unmanaged table in Snowflake to read data from Table1. |
| 136 | + |
| 137 | +") |
| 138 | + |
| 139 | +## Security and access control |
| 140 | + |
| 141 | +### Credential vending |
| 142 | + |
| 143 | +To secure interactions with service connections, Polaris vends temporary storage credentials to the query engine during query |
| 144 | +execution. These credentials allow the query engine to run the query without requiring access to your cloud storage for |
| 145 | +Iceberg tables. This process is called credential vending. |
| 146 | + |
| 147 | +As of now, the following limitation is known regarding Apache Iceberg support: |
| 148 | + |
| 149 | +- **remove_orphan_files:** Apache Spark can't use credential vending |
| 150 | + for this due to a known issue. See [apache/iceberg#7914](https://github.com/apache/iceberg/pull/7914) for details. |
| 151 | + |
| 152 | +### Identity and access management (IAM) |
| 153 | + |
| 154 | +Polaris uses the identity and access management (IAM) entity to securely connect to your storage for accessing table data, Iceberg |
| 155 | +metadata, and manifest files that store the table schema, partitions, and other metadata. Polaris retains the IAM entity for your |
| 156 | +storage location. |
| 157 | + |
| 158 | +### Access control |
| 159 | + |
| 160 | +Polaris enforces the access control that you configure across all tables registered with the service and governs security for all |
| 161 | +queries from query engines in a consistent manner. |
| 162 | + |
| 163 | +Polaris uses a role-based access control (RBAC) model that lets you centrally configure access for Polaris service principals to catalogs, |
| 164 | +namespaces, and tables. |
| 165 | + |
| 166 | +Polaris RBAC uses two different role types to delegate privileges: |
| 167 | + |
| 168 | +- **Principal roles:** Granted to Polaris service principals and |
| 169 | + analogous to roles in other access control systems that you grant to |
| 170 | + service principals. |
| 171 | + |
| 172 | +- **Catalog roles:** Configured with certain privileges on Polaris |
| 173 | + catalog resources and granted to principal roles. |
| 174 | + |
| 175 | +For more information, see [Access control]({{% ref "access-control" %}}). |
| 176 | + |
| 177 | +## Legal Notices |
| 178 | + |
| 179 | +Apache®, Apache Iceberg™, Apache Spark™, Apache Flink®, and Flink® are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. |
| 180 | + |
| 181 | + |
| 182 | +<!-- |
| 183 | +Testing the `releaseVersion` shortcode here: version is: {{< releaseVersion >}} |
| 184 | +--> |
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