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नेस्सी कैटलॉग

विहंगावलोकन​

प्रोजेक्ट नेस्सी एक ओपन-सोर्स है लेन-देन संबंधी डेटा कैटलॉग that brings Git-like version control to data lakes. It enables you to manage multiple versions of your data using branches, tags, and commits, similar to how Git manages source code.

With Ilum’s integration, you can leverage Nessie’s version control features directly in your Spark environment. This allows you to branch, tag, and merge data changes safely and efficiently.

Unlike traditional Hive or Glue catalogs, which only track the latest state of each table, Nessie records कमिट के रूप में सभी परिवर्तन in a timeline. Each commit represents a consistent snapshot of your data lake. Changes are isolated until committed, ensuring incomplete or in-progress updates are never visible to other users or jobs. Once finalized, changes become atomically visible, guaranteeing consistency.

Key Features: Nessie vs. Traditional Catalogs​

लक्षणTraditional Catalogsनेस्सी कैटलॉग
BranchingनहींYes (Git-like)
Isolated EnvironmentsManual/ComplexSimple, via branches
Commit History & Time TravelLimited/Per-tableFull catalog history
मल्टी-टेबल लेनदेननहींYes (atomic commits)
Collaboration & Governanceयथासंभव न्‍यूनतमBuilt-in, audit log

Highlights​

  • Branching: Create multiple isolated branches (e.g., मुख्य, देव, staging) without duplicating data. Branches are lightweight pointers to metadata snapshots.
  • पृथक वातावरण: Use the same data lake for dev, staging, and prod by isolating changes in branches. No need for separate catalogs or data copies.
  • प्रतिबद्ध इतिहास और समय यात्रा: Nessie maintains a unified commit log. Inspect, audit, or time-travel to any previous state by commit hash or timestamp.
  • परमाणु मल्टी-टेबल लेनदेन: Commit changes across multiple tables as a single atomic operation. All succeed or none do.
  • Collaboration & Governance: Work on separate branches, merge changes, and track who changed what and when. Enables safe experimentation and robust auditability.

Core Concepts​

शाखाएँ​

एक शाखा is an independent line of development for your data catalog. Branches start as copies of existing branches and track changes separately. They are lightweight, referencing the same data files but different metadata. The default branch is usually मुख्य.

टैग​

एक टैग is a read-only label pointing to a specific commit. Use tags to mark stable versions or important milestones (e.g., v1.0 के अनुसार, 2025-06-रिलीज़). Tags are immutable bookmarks.

Commits​

एक करना is a set of changes recorded as a single atomic unit. Each commit has a unique ID, timestamp, author, and optional message. The commit log provides full catalog versioning.

इलम में नेस्सी का उपयोग करना​

चेतावनी

Nessie is not enabled by default in Ilum. To enable it, see the production पृष्ठ।

इलम समर्थन करता है प्रोजेक्ट नेस्सी as a catalog for version-controlled data management. When using Ilum notebooks or Spark jobs with Apache Iceberg, Git-like operations (branching, merging, tagging) can be performed directly via SQL.

There are two ways to wire Nessie into a cluster: the chart-managed flow, recommended for Helm deployments, and the manual flow, for self-managed Spark images or clusters configured outside the chart.

नोट

Nessie SQL operations (USE BRANCH, CREATE BRANCH, MERGE BRANCH, and the rest of the walkthrough below) are supported on both the Spark 3.5 and Spark 4.x image lines. Use the matching ilum/spark:-nessie image, for example ilum/spark:3.5.8-nessie नहीं तो ilum/spark:4.1.2-nessie. The Spark 4.x image ships nessie-spark-extensions-4.0_2.13, which is ABI-compatible with the Spark 4.1 line (no native 4.1 build is published yet), mirroring the iceberg-spark-runtime-4.0_2.13 it pairs with.

When Ilum is deployed with the Helm chart, the Nessie catalog is configured declaratively. Enable the metastore and set its type to नेस्सी में इलम कोर values (the example uses the umbrella-chart key; in the standalone helm_core chart the same keys live at the top level):

इलम कोर:
  मेटास्टोर:
    सक्षम: सच्चा
    प्रकार: नेस्सी
    नेस्सी:
      address: एचटीटीपी://ilum-नेस्सी:19120
      warehouseDir: s3a://ilum-data/nessie_catalog/
      s3Endpoint: एचटीटीपी://ilum-objectstorage:9000/
      s3PathStyleAccess: सच्चा
      संदर्भ: मुख्य
      catalogName: nessie_catalog
नेस्सी:
  सक्षम: सच्चा

The Iceberg + Nessie catalog wiring — spark.sql.एक्सटेंशनवही SparkCatalog provider, catalog-impl (NessieCatalog), and io-impl (S3FileIO) — is generated by ilum-core under the configured catalogName; it does not need to be set in values. Ilum injects it, together with the connection settings above (URI, संदर्भ, warehouse, S3 endpoint, path-style, and region) and the catalog's S3 credentials (taken from the cluster's object-storage credentials, never persisted on the metastore), into every Spark submission on a cluster that has the metastore attached. No catalog wiring, extraJavaOptions, or credentials need to be set on the cluster or in the notebook session — a chart-managed Nessie catalog works out of the box.

के साथ metastore.enabled: true, the bundled चूक cluster is attached to this metastore automatically, so jobs on it resolve the catalog out of the box. The catalog is addressed by metastore.nessie.catalogName (default nessie_catalog); tables are referenced as nessie_catalog..

throughout the SQL examples below.

To attach the metastore to another cluster, open its Edit Cluster tab and select Nessie in the General metastore dropdown:

Catalog Selection

Manual configuration​

For a cluster running a self-managed Spark image, or when Nessie is configured outside the chart, the nessie_catalog must be pre-configured in the Spark session.

Make sure the Spark image used in the cluster has the Nessie client installed. In particular, the following are required:

  • Iceberg Spark Runtime (org.apache.iceberg:iceberg-spark-runtime-_) - Required for Nessie support.
  • Iceberg AWS Bundle (org.apache.iceberg:iceberg-aws-bundle) - Required for S3 support.
  • Nessie SQL Extensions (org.projectnessie.nessie-integrations:nessie-spark-extensions-_) - Required for Nessie-specific SQL operations.

इलम का custom Spark image for Nessie: ilum/spark:-nessie includes all the required dependencies.

नोट

When the catalog उरी targets the Nessie server's /api/v2 endpoint, also set spark.sql.catalog..client-api-version=2. The Iceberg-bundled Nessie client otherwise defaults to API v1 and the first catalog call fails with NessieApiCompatibilityException: API version mismatch.

चेतावनी

Ilum’s spark-nessie image does not include any Delta table dependencies, so the default cluster configuration for Delta tables must be removed when using this image (on a chart deployment, override these via कुबेरनेट्स.डिफ़ॉल्टक्लस्टर.कॉन्फ़िग). In particular:

नाममूल्य
spark.sql.कैटलॉग.स्पार्क_कैटलॉगorg.apache.spark.sql.delta.catalog.DeltaCatalog
spark.sql.एक्सटेंशनio.delta.sql.DeltaSparkSessionExtension

Nessie Walkthrough​

In the beginning, it is recommended to create anything inside the main branch so that you avoid problems with merging into an empty branch:

बनाना सारणी nessie_catalog.उपयोगकर्ताओं(
    user_id आईएनटी,
    user_name वरचर(20)  
);

Create a Branch​

बनाना शाखा देव में nessie_catalog से मुख्य;

And to verify everything, list all branches and tags:

तालिका संदर्भ में nessie_catalog;

Work on a Branch​

Create a table and insert data in the देव branch with the fully qualified name (@ नहीं तो @):

बनाना सारणी nessie_catalog.`sales@dev`(
    sale_timestamp CHAR(10),
    sale_amount आईएनटी,
    payment_method वरचर(20)
);

अंतःस्‍थापित करना में nessie_catalog.`sales@dev` मान
    ('2025-06-01', 1000, 'ऑनलाइन'),
    ('2025-06-02', 1500, 'InStore'),
    ('2025-06-03', 800, 'ऑनलाइन'),
    ('2025-06-04', 1200, 'Mobile'),
    ('2025-06-05', 950, 'InStore');
चुनना गिनना(*) से nessie_catalog.`sales@dev`;

Or use the प्रयोग statement to switch a context to a specific branch:

प्रयोग शाखा देव में nessie_catalog;
चुनना गिनना(*) से nessie_catalog.बिक्री;
नोट

Because Ilum’s SQL executor treats each query as a stateless entity, using the प्रयोग statement requires executing all related statements together.
To do this, select the entire query block in the editor and then press अमल.

And show the log of all commits done:

प्रदर्शन LOG पर देव में nessie_catalog;

Merge Branches​

डुबो शाखा देव में मुख्य में nessie_catalog;
प्रदर्शन तालिकाओं में nessie_catalog;
नोट

If you see an error of No common ancestor in parents of and , this can mean that the branch you are trying to merge into is empty. This will cause the merge to fail, even if the branch you are trying to merge was correctly created from the parent branch.

Cataloging Nessie Tables in OpenMetadata​

Iceberg tables managed in Nessie can be surfaced in OpenMetadata — Ilum's metadata catalog and governance layer — so that branched, committed, version-controlled tables become discoverable, classifiable, and lineage-connected assets alongside the rest of the data platform.

OpenMetadata reads Nessie through its Iceberg-REST endpoint (base URI http://ilum-nessie:19120/iceberg), cataloging the tables visible on a single reference. The reference is selected by the warehouse (default nessie_catalog → ref मुख्य), not by the URI path. Nessie's branch/tag/commit history is flattened — OpenMetadata sees only the current state of that one reference, not the version timeline. The integration is opt-in and enabled with two values:

नेस्सी:
  सक्षम: सच्चा
openmetadataBootstrap:
  सेवाएँ:
    हिमशैल:
      सक्षम: सच्चा

For the connector details, branch-semantics caveats, object-storage credential note, and full enabling reference, see Iceberg tables via Project Nessie on the OpenMetadata page.

नोट

This integration is newly added and opt-in. Its configuration is validated against the chart; the end-to-end result (a Nessie-committed Iceberg table appearing in the OpenMetadata catalog) is pending live verification. Treat it as a preview until confirmed.

सबसे सही तरीके​

  • Develop in Isolation: Use branches for development or experiments. Promote changes through a hierarchy (e.g., dev → staging → main).
  • Merge Frequently: Merge changes regularly to minimize conflicts.
  • शाखाओं को अल्पकालिक रखें: Remove feature branches after merging.
  • Avoid Conflicts: Sync your branch with the latest target branch before merging.
  • Tag Milestones: Use tags for stable releases or important checkpoints.
  • Document Changes: Add commit messages for traceability.

और जानो​

For advanced SQL operations and the full Nessie Spark SQL reference, see:
👉 Nessie Spark SQL संदर्भ

Nessie with Ilum combines Spark’s power with Git-like data management, enabling robust “data as code” workflows for your lakehouse.

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