Databricks Runtime 18 (Beta)

This page contains unified release notes for Databricks Runtime 18, powered by Apache Spark 4.1.0. It lists all features, behavior changes, and fixes shipped throughout the Databricks Runtime 18 release cycle.

note

Releases are staged. Your Databricks account might not update for a few days after the initial release date.

About unified release notes

Databricks releases features incrementally throughout the release cycle without changing the version number. Rather than separate pages for each minor version, all updates appear on this single page as dated entries. Clusters receive updates when they restart.

Databricks Runtime 18 is the first release to use this unified format. Previously, each feature version (18.0, 18.1, 18.2) had its own release notes page. Those pages remain available for reference. Features that would previously have shipped as 18.3 or later now ship as dated updates to Databricks Runtime 18.

• Databricks Runtime 18.0
• Databricks Runtime 18.1
• Databricks Runtime 18.2

In the future, Databricks Runtime versions will follow a lifecycle from Beta (early evaluation) through GA (feature development, approximately six months) to LTS (long-term support, three years of stability and security fixes). Because 18.0 through 18.2 shipped under the previous model, Databricks Runtime 18 is a transitional release that will move directly from Beta to LTS. For full lifecycle details, see Databricks Runtime support lifecycles.

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Databricks Runtime 18: May 18, 2026

Behavioral changes

Review the following changes, which take effect when clusters restart on this runtime.

• CREATE OR REPLACE TABLE: CREATE OR REPLACE TABLE now preserves existing column and table comments by default. Previously, comments were dropped when recreating a table. Managed tables and views now match the existing behavior of materialized views and streaming tables.
• DataFrame by-name writes: writeTo().append(), writeTo().overwrite(), writeTo().overwritePartitions(), and write.mode("append").saveAsTable() now automatically cast type-compatible columns (for example, int to long) to match the target Delta table schema. Previously, these operations failed with a DELTA_FAILED_TO_MERGE_FIELDS error when column types were compatible but not identical. Behavior now matches SQL INSERT INTO ... BY NAME. save() and saveAsTable() in overwrite mode are not affected.
• ALTER TABLE SET TBLPROPERTIES for pipelines.pipelineId: ALTER TABLE <table> SET TBLPROPERTIES('pipelines.pipelineId' = '<pipeline-id>') now attempts to make the specified table eligible for writes by the pipeline. Previously, setting this property on a regular table had no effect. If the table isn't eligible for pipeline writes, the command throws SETTING_PIPELINES_PIPELINE_ID_NOT_SUPPORTED.
• cloud_files_state: The cloud_files_state table-valued function (TVF) now includes a discovery_mode column showing how Auto Loader discovered each file. Files discovered before upgrading have a null value in this column.
• DESCRIBE EXTENDED AS JSON: Now includes predictive optimization evaluation results in its output. Previously, this information wasn't returned in the JSON output.
• Metric view window measures: Now return correct results when queries use GROUP BY, IN/BETWEEN filters, or mixed predicates on the window's order column. Previously, these filter patterns could produce incorrect results.

New features and improvements

The following features and improvements are available in this release.

• Cluster libraries: When you install PyPI libraries, wheels, or requirements.txt files on a cluster, the Libraries tab and Libraries REST API now display all resolved and installed packages, including transitive dependencies. For installations that resolve more than 500 packages, the list is truncated. The full installation report is available in the cluster's driver logs.
• Auto CDC from snapshot with SQL syntax: Lakeflow Spark Declarative Pipelines now supports Auto CDC from snapshot using SQL syntax. Previously, this feature was only available through the Python API. Use CREATE STREAMING TABLE ... FLOW AUTO CDC FROM SNAPSHOT to process snapshot sources (such as Delta tables, cloud storage, or JDBC) one snapshot at a time. Both SCD Type 1 (default) and SCD Type 2 are supported.
• array_sort with custom comparators: Photon now accelerates array_sort expressions that use custom comparators to sort arrays of structs by one or more fields. Previously, these expressions fell back to non-Photon execution. To enable this optimization, set spark.databricks.photon.rewriteArraySortComparator.enabled to true.

Apache Spark fixes and improvements

This release includes the following bug fixes and improvements made to Spark:

• SQL queries now support a QUALIFY clause, which lets you filter on window function results directly in the query. Previously this required wrapping the query in a subquery.
• spark.read.json, spark.read.csv, and spark.read.xml now accept a DataFrame as input, so you can parse in-memory data without saving it to a file first.
• DataFrame.changes() is now available for reading change data capture (CDC) output through the DataFrame API.
• When a DataFrame column is referenced from the wrong DataFrame, the error now names the specific column. You can also set spark.sql.columnResolution.strict to make Spark enforce stricter column matching and catch these mistakes earlier.
• MERGE INTO schema evolution now works correctly when the statement includes WHEN MATCHED THEN DELETE or references nested columns by alias. Previously, these combinations could fail or silently produce wrong results.
• SHOW COLLATIONS lists all supported collations and their properties, which is useful when choosing a collation for text sorting or comparison.
• Spark's query optimizer now correctly estimates how much data filters will reduce. Incorrect estimates previously caused Spark to pull large tables fully into memory during joins, leading to out-of-memory errors.
• Queries with multiple COUNT(DISTINCT) expressions run faster because Spark now reduces the data earlier in the execution plan instead of expanding it first.
• Python UDFs that use the Arrow optimization no longer perform an unnecessary data format conversion, reducing overhead.
• Stream-stream non-outer joins can now produce output in Update mode, not just Append mode, which allows them to write to more output destinations.
• JDBC connections are now properly closed when a task is cancelled. Previously, cancellation could leave a connection open, causing later tasks to hang.
• array_insert no longer produces wrong results when given a very large negative number as the insert position.

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Databricks Runtime 18: May 4, 2026

Behavioral changes

Review the following changes, which take effect when clusters restart on this runtime.

• XPath: When evaluating XPath over XML, Databricks no longer loads external Document Type Definitions (DTDs). Queries that previously failed only because of an unreachable external DTD reference can now succeed.
• NULL struct behavior with schema evolution: For INSERT, MERGE, and streaming writes that use schema evolution, a NULL struct in the source is now stored as NULL in the target. Previously, NULL structs were incorrectly materialized as non-null structs with every field set to NULL. Update any code that relied on receiving a non-null struct with all-NULL fields — those cases now return a NULL struct.
• NATURAL JOIN: Now correctly uses case-insensitive column matching when spark.sql.caseSensitive is false (the default). Previously, columns that differed only in case (for example, ID vs id) were not recognized as matching, causing NATURAL JOIN to silently produce cross-join results. This fix aligns NATURAL JOIN behavior with USING joins.
• AWS SDK v1 dependencies: Now shaded and no longer directly available on the classpath. If your code depends on AWS SDK v1 libraries previously provided by Databricks Runtime, add them as explicit dependencies in your project.
• SQL UDF dependency validation in Unity Catalog: Unity Catalog now enforces dependency validation for SQL user-defined functions to prevent access control bypass. SQL UDFs with invalid dependency configurations are blocked from execution.
• LEFT OUTER JOIN LATERAL: A bug that incorrectly dropped rows has been fixed. Queries using this construct now return correct results. To temporarily revert to the previous behavior, set spark.databricks.sql.optimizer.lateralJoinPreserveOuterSemantic to true.
• regr_r2: Now correctly treats the first parameter as the dependent variable. Queries that relied on the previous incorrect behavior return different results.
• Hyperbolic functions: sinh, cosh, tanh, and related hyperbolic functions now return Infinity instead of throwing an overflow error when given very large inputs.
• asinh and acosh: Now use the fdlibm algorithm for cross-engine consistency. Results might differ slightly from previous versions for edge-case inputs.
• LIKE pattern matching: Now correctly handles supplementary Unicode characters (code points above U+FFFF). Patterns that previously matched or failed incorrectly for these characters now return correct results.
• VOID (NullType) columns: Delta tables now support VOID (NullType) columns. VOID columns are no longer dropped from the table schema upon reads. Writes are unaffected.

New features and improvements

The following features and improvements are available in this release.

• CREATE OR REPLACE TEMP TABLE: Now supported, allowing you to create or replace temporary tables in a single statement.
• agg(): Now available as an alias for the measure() function. Existing queries using measure() continue to work without modification.
• pyspark.pipelines.testing: Now available as a convenience alias for dlt.testing APIs.
• Auto Loader listing performance: Auto Loader now uses a more efficient listing method that improves listing speed for cloud storage sources. If your stream triggers overlap due to long-running listing operations, this optimization can result in increased cloud listing API costs.
• DESCRIBE HISTORY write option flags: Delta table history (DESCRIBE HISTORY) now includes write option flags in operationParameters for WRITE and REPLACE TABLE operations. Flags appear only when true: isDynamicPartitionOverwrite, canOverwriteSchema, canMergeSchema, predicate, and isV1WriterSaveAsTableOverwrite.
• Structured Streaming rewind and replay: Structured Streaming now supports rewind and replay, enabling reprocessing from an earlier point in the stream to recover from failures such as schema changes or logic errors, without a full state reset.
• SparkSession.emptyDataFrame: Now available as a convenience API for creating an empty DataFrame with no columns and no rows.
• TIMESTAMP WITH LOCAL TIME ZONE: Now supported as a SQL syntax alias for the TIMESTAMP_LTZ type.
• to_json sortKeys option: The to_json function now accepts a sortKeys option to produce JSON output with keys in sorted order.
• spark.catalog.*: API methods now have feature parity with their equivalent DDL commands for catalog, schema, and table operations.
• [Security fix] Operating system security updates.

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Databricks Runtime 18: April 20, 2026

• Fixed the CRS spatial reference authority for the GEOMETRY(102100) type. The authority is now reported as ESRI:102100 instead of EPSG:102100.
• [Security fix] Operating system security updates.

---

Databricks Runtime 18: April 2, 2026

• Improved error handling for queries writing data to Delta tables that contain a VOID (NullType) column inside a user-defined type (UDT).
• JDBC streaming sink connections now apply a 30-second socket timeout, retry logic with exponential backoff for transient errors (connection failures, deadlocks, rate limiting), and graceful rollback on broken connections.
• Fixed SQL text corruption that occurred when using Unicode characters in parameterized queries.
• SHOW CREATE TABLE now produces correct output for tables and views with a non-default collation.
• [Security fix] Operating system security updates.

---

Databricks Runtime 18: March 11, 2026

Behavioral changes

Review the following changes, which take effect when clusters restart on this runtime.

• Observation metric errors: No longer cause query execution failures. Previously, errors in OBSERVE clauses (such as division by zero) could block or fail the entire query. Now, the query completes successfully and the error is raised when you call observation.get.
• FILTER clause for MEASURE: MEASURE aggregate functions now support FILTER clauses. Previously, filters were silently ignored.
• DESCRIBE FLOW: The DESCRIBE FLOW command is now available. If you have a table named flow, use DESCRIBE schema.flow, DESCRIBE TABLE flow, or DESCRIBE `flow` with backticks.
• SpatialSQL Boolean set operations: ST_Difference, ST_Intersection, and ST_Union use a new implementation with the following improvements:
  • Valid input geometries always produce a result and no longer raise errors.
  • Approximately 2x faster performance.
  • Results are normalized for consistent, comparable output.
• Exception types for SQLSTATE: Exception types are updated to support SQLSTATE. If your code parses exceptions by string matching or catches specific exception types, update your error handling logic.
• Automatic streaming type widening: Streaming reads on Delta tables automatically handle column type widening. To require manual acknowledgement, set spark.databricks.delta.typeWidening.enableStreamingSchemaTracking to true.

New features and improvements

The following features and improvements are available in this release.

• Auto Loader file events by default: Auto Loader uses file events by default when loading from an external location with file events enabled, which reduces list operations and cost compared to directory listing. See Auto Loader with file events overview. To use directory listing instead, set useManagedFileEvents to false.

• Schema evolution with INSERT: Use the WITH SCHEMA EVOLUTION clause with SQL INSERT statements to automatically evolve the target table's schema during insert operations. Supported for INSERT INTO, INSERT OVERWRITE, and INSERT INTO ... REPLACE. For example:

  SQL

  INSERT WITH SCHEMA EVOLUTION INTO students TABLE visiting_students_with_additional_id;

• Delta Sharing multi-statement transactions: Delta Sharing tables that use pre-signed URL or cloud token sharing modes support multi-statement transactions. On first access within a transaction, the table version is pinned and reused for all subsequent reads in that transaction.

• parse_timestamp: The parse_timestamp SQL function parses timestamp strings using multiple patterns, with Photon engine support for improved performance.

• max_by and min_by with optional limit: The aggregate functions max_by and min_by now accept an optional third argument limit (up to 100,000). When provided, the functions return an array of up to limit values, simplifying top-K and bottom-K queries without window functions or CTEs.

• DATETIMEOFFSET for Azure Synapse: The DATETIMEOFFSET data type is supported for Microsoft Azure Synapse connections.

• Google BigQuery table comments: Google BigQuery table descriptions are resolved and exposed as table comments.

• IGNORE NULLS/RESPECT NULLS for array_agg and collect_list: The array_agg and collect_list aggregate functions now support IGNORE NULLS and RESPECT NULLS clauses.

• PIVOT aliases: The PIVOT clause now supports aliases, allowing you to rename pivot column expressions in the output.

• SQL scripting CURSOR variables: SQL scripting now supports CURSOR variables for iterating over a query result set row by row within a scripting block.

• Vector math aggregate functions: New vector math aggregate functions are available: vector_avg, vector_sum, vector_norm, and vector_normalize. These functions operate on dense vector columns and support ML workloads.

• Trigger.AvailableNow in Python streaming readers: Python data source streaming readers now support Trigger.AvailableNow and Admission Control, enabling one-time batch processing of all available data.

• State repartition API in PySpark: The state repartition API for TransformWithState streaming operators is now available in PySpark, in addition to Scala. See On-demand state repartitioning for stateful streaming queries.

• applyInPandas performance fix: A 3x performance regression in applyInPandas for large groups has been resolved.

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Databricks Runtime 18: March 10, 2026

• Error messages for scalar subqueries used with EXEC IMMEDIATE now identify the specific cause more clearly.
• Fixed a race condition in streaming checkpoint log compaction that could cause non-deterministic behavior in Structured Streaming queries.
• [Security fix] Operating system security updates.

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Databricks Runtime 18: February 26, 2026

• SET METADATA ON COLUMN and UNSET METADATA ON COLUMN SQL commands are now available for managing semantic metadata on Unity Catalog table columns. Use SET METADATA ON COLUMN to attach properties (display_name, format, and synonyms) to columns. Use UNSET METADATA ON COLUMN to remove previously set metadata properties.
• DESCRIBE TABLE now includes a metadata column displaying column-level semantic metadata as a JSON string.
• Fixed a PySpark import error in Windows environments caused by a missing UnixStreamServer.
• [Security fix] Operating system security updates.

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Databricks Runtime 18: February 19, 2026

• When inferring the schema of Excel files, string cells are now inferred as Spark StringType, respecting the cell type set in Excel. Previously, strings with numeric values were auto-cast to narrower types like Long or Decimal. Update code that relied on the previous behavior.
• DataFrame.toJSON() is now available in the Python Spark Connect client.
• [Security fix] Operating system security updates.

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Databricks Runtime 18: January 27, 2026

• Auto Loader now reports batchSizeNumFiles, batchSizeNumBytes, and file processing states (numFilesProcessed, numFilesSkippedCorrupted, numFilesSkippedMissing, numFilesUnknownState) as metrics.
• INSERT INTO ... BY NAME now supports the REPLACE WHERE clause.
• The configuration property spark.sql.xml.legacyXMLParser.enabled has been renamed to spark.sql.legacy.useLegacyXMLParser. Update any cluster or session configurations that use the old name.
• When spark.task.resource.gpu.amount is greater than 1, Torch Distributor now launches one torchrun process per GPU rather than per task.
• [Security fix] Operating system security updates.

---

Databricks Runtime 18: January 15, 2026

Databricks Runtime 18 is now in feature development, powered by Apache Spark 4.1.0. This version incorporates all features, improvements, and bug fixes from all previous Databricks Runtime releases.

Behavioral changes

Review the following changes, which take effect when clusters restart on this runtime.

• JDK 21: Databricks Runtime 18 uses JDK 21 as the default Java Development Kit. JDK 21 is generally available and is a long-term support (LTS) release. Previously, the default was JDK 17. Notable changes:

  • Double.toString() and Float.toString() now produce shortest unique string representations, which might differ from JDK 17 outputs in some edge cases.
  • Thread.stop(), Thread.suspend(), and Thread.resume() now throw UnsupportedOperationException.
  • Updated locale data (CLDR v42) might affect date, time, and number formatting.

  If you encounter compatibility issues, fall back to JDK 17. For information about configuring JDK versions, see Create a cluster with a specific JDK version.

• FSCK REPAIR TABLE: Now includes an initial metadata repair step before checking for missing data files. The command works on tables with corrupt checkpoints or invalid partition values.

• Spark Connect Scala nullability: The nullability of array and map types is now preserved for typed literals in the Spark Connect Scala client. Previously, elements of arrays and values of maps were always nullable.

• FSCK REPAIR TABLE DRY RUN: The dataFilePath column in the FSCK REPAIR TABLE DRY RUN output schema is now nullable to support reporting new issue types where the data file path isn't applicable.

• SHOW TABLES DROPPED: Now correctly respects the LIMIT clause.

• Python UDF execution: Unity Catalog Python UDFs now use Apache Arrow as the default interchange format, improving overall performance. As part of this change, TIMESTAMP values passed to Python UDFs no longer include timezone information in the datetime object's tzinfo attribute. The timestamp values themselves remain in UTC, but the timezone metadata is now dropped. If your UDF relies on the timezone information, restore it with date = date.replace(tzinfo=timezone.utc). For more information, see Timestamp timezone behavior for inputs.

• Time travel and VACUUM retention: Databricks now blocks time travel queries beyond the deletedFileRetentionDuration threshold for all tables. The VACUUM command ignores the retention duration argument except when the value is 0 hours. You can't set deletedFileRetentionDuration larger than logRetentionDuration or vice versa.

• BinaryType in PySpark: In PySpark, BinaryType now consistently maps to Python bytes. Previously, PySpark mapped BinaryType to either bytes or bytearray depending on the context. To restore the old behavior, set spark.sql.execution.pyspark.binaryAsBytes to false.

• NULL structs in Delta MERGE and UPDATE: Now preserved as NULL in Delta MERGE, UPDATE, and streaming write operations that include struct type casts. Previously, NULL structs were expanded to structs with NULL fields.

• Partition column materialization: Partitioned Delta tables now materialize partition columns in newly written Parquet data files. Previously, partition values were stored in the Delta transaction log metadata and reflected in directory paths, but not written as columns in the Parquet files themselves. This change aligns with Apache Iceberg and UniForm behavior and might affect workloads that directly read Parquet files written by Delta Lake.

• Timestamp partition timezone: Timestamp partition values were previously converted to UTC using the JVM timezone instead of the spark.sql.session.timeZone configuration. Timestamp partition values are now correctly adjusted using the Spark session timezone setting.

• DESCRIBE TABLE metadata column: The output of DESCRIBE TABLE [EXTENDED] now includes a new metadata column for all table types. This column contains semantic metadata (display name, format, and synonyms) defined on the table as a JSON string.

New features and improvements

The following features and improvements are available in this release.

• SQL scripting: The SQL scripting feature is now generally available.
• Shared isolation for Unity Catalog Python UDFs: Unity Catalog Python UDFs with the same owner can now share an isolation environment by default. This improves performance and reduces memory usage by reducing the number of separate environments launched. To ensure a UDF always runs in a fully isolated environment, add the STRICT ISOLATION characteristic clause. See Environment isolation.
• SQL window functions in metric views: You can now use SQL window functions in metric views to calculate running totals, rankings, and other window-based calculations.
• Dynamic shuffle partitions in stateless streaming: You can now change the number of shuffle partitions in stateless streaming queries without restarting the query.
• AQE and AOS in stateless streaming: Adaptive Query Execution (AQE) and auto-optimized shuffle (AOS) are now supported in stateless streaming queries.
• Parameter markers: You can now use named (:param) and unnamed (?) parameter markers virtually anywhere a literal value of the appropriate type can be used. This includes DDL statements such as CREATE VIEW v AS SELECT ? AS c1, column types DECIMAL(:p, :s), or COMMENT ON t IS :comment. See Parameter markers for details.
• IDENTIFIER clause: The reach of the IDENTIFIER clause, which casts strings to SQL object names, has been expanded to nearly everywhere an identifier is permitted. See IDENTIFIER clause for details.
• BITMAP_AND_AGG: The existing library of BITMAP functions now includes a new BITMAP_AND_AGG function.
• Theta sketch functions: You can now use a new library of functions for approximate distinct count and set operations using Datasketches Theta Sketch. See theta_sketch_agg and related functions.
• KLL sketch functions: You can now use a new library of functions for approximate quantile computation using KLL Sketches. See kll_sketch_agg_bigint and related functions.
• New geospatial functions: st_azimuth, st_boundary, st_closestpoint, and st_geogfromewkt are now available.
• GeometryType and GeographyType: Apache Spark now supports native GeometryType and GeographyType data types in the PySpark and Java APIs. These types support Arrow serialization and Parquet read and write, and are distinct from the SQL geospatial functions.
• approx_top_k: The new approx_top_k aggregate function returns the approximate top-K most frequent values in a column using a space-efficient sketch algorithm.
• Spark Connect JDBC driver: Apache Spark now includes a JDBC driver for Spark Connect, enabling JDBC-based clients and tools to connect to Spark through the Spark Connect protocol.
• Iterator[pandas.DataFrame] in applyInPandas: DataFrame.applyInPandas now accepts a function with an Iterator[pandas.DataFrame] signature, reducing overhead when processing large groups by streaming data in batches.
• Check constraints: Now support null value comparisons in the constraint expression.
• State repartition API for TransformWithState: A new state repartition API is available for TransformWithState streaming operators in Scala, allowing you to change the key partitioning of stateful data across query restarts. See On-demand state repartitioning for stateful streaming queries.
• Python 3.14 in pyspark-connect: pyspark-client and pyspark-connect now support Python 3.14.

Library upgrades

• Upgraded Python libraries:

  • anyio from 4.6.2 to 4.7.0
  • asttokens from 2.0.5 to 3.0.0
  • azure-core from 1.34.0 to 1.37.0
  • azure-mgmt-core from 1.5.0 to 1.6.0
  • azure-storage-blob from 12.23.0 to 12.28.0
  • azure-storage-file-datalake from 12.17.0 to 12.22.0
  • boto3 from 1.36.2 to 1.40.45
  • botocore from 1.36.3 to 1.40.45
  • certifi from 2025.1.31 to 2025.4.26
  • click from 8.1.7 to 8.1.8
  • cryptography from 43.0.3 to 44.0.1
  • Cython from 3.0.12 to 3.1.5
  • databricks-sdk from 0.49.0 to 0.67.0
  • Deprecated from 1.2.13 to 1.2.18
  • executing from 0.8.3 to 1.2.0
  • fastapi from 0.115.12 to 0.128.0
  • filelock from 3.18.0 to 3.17.0
  • google-api-core from 2.20.0 to 2.28.1
  • google-auth from 2.40.0 to 2.47.0
  • google-cloud-core from 2.4.3 to 2.5.0
  • google-cloud-storage from 3.1.0 to 3.7.0
  • google-crc32c from 1.7.1 to 1.8.0
  • google-resumable-media from 2.7.2 to 2.8.0
  • h11 from 0.14.0 to 0.16.0
  • httpcore from 1.0.2 to 1.0.9
  • httpx from 0.27.0 to 0.28.1
  • isodate from 0.6.1 to 0.7.2
  • Jinja2 from 3.1.5 to 3.1.6
  • jupyter-events from 0.10.0 to 0.12.0
  • jupyter-lsp from 2.2.0 to 2.2.5
  • jupyter_server from 2.14.1 to 2.15.0
  • jupyter_server_terminals from 0.4.4 to 0.5.3
  • mistune from 2.0.4 to 3.1.2
  • mlflow-skinny from 3.0.1 to 3.8.1
  • mmh3 from 5.1.0 to 5.2.0
  • msal from 1.32.3 to 1.34.0
  • nbclient from 0.8.0 to 0.10.2
  • nbconvert from 7.16.4 to 7.16.6
  • nodeenv from 1.9.1 to 1.10.0
  • notebook_shim from 0.2.3 to 0.2.4
  • opentelemetry-api from 1.32.1 to 1.39.1
  • opentelemetry-sdk from 1.32.1 to 1.39.1
  • opentelemetry-semantic-conventions from 0.53b1 to 0.60b1
  • platformdirs from 3.10.0 to 4.3.7
  • prometheus_client from 0.21.0 to 0.21.1
  • proto-plus from 1.26.1 to 1.27.0
  • psycopg2 from 2.9.3 to 2.9.11
  • pyarrow from 19.0.1 to 21.0.0
  • Pygments from 2.15.1 to 2.19.1
  • pyiceberg from 0.9.0 to 0.10.0
  • python-lsp-server from 1.12.0 to 1.12.2
  • rope from 1.12.0 to 1.13.0
  • s3transfer from 0.11.3 to 0.14.0
  • scipy from 1.15.1 to 1.15.3
  • setuptools from 74.0.0 to 78.1.1
  • six from 1.16.0 to 1.17.0
  • sqlparse from 0.5.3 to 0.5.5
  • stack-data from 0.2.0 to 0.6.3
  • starlette from 0.46.2 to 0.50.0
  • tornado from 6.4.2 to 6.5.1
  • types-python-dateutil from 2.9.0.20241206 to 2.9.0.20251115
  • uvicorn from 0.34.2 to 0.40.0
  • webcolors from 24.11.1 to 25.10.0

• Upgraded R libraries:

  • arrow from 19.0.1 to 22.0.0
  • base from 4.4.2 to 4.5.1
  • bigD from 0.3.0 to 0.3.1
  • broom from 1.0.7 to 1.0.10
  • clock from 0.7.2 to 0.7.3
  • commonmark from 1.9.5 to 2.0.0
  • compiler from 4.4.2 to 4.5.1
  • credentials from 2.0.2 to 2.0.3
  • curl from 6.4.0 to 7.0.0
  • data.table from 1.17.0 to 1.17.8
  • datasets from 4.4.2 to 4.5.1
  • dbplyr from 2.5.0 to 2.5.1
  • devtools from 2.4.5 to 2.4.6
  • diffobj from 0.3.5 to 0.3.6
  • digest from 0.6.37 to 0.6.39
  • downlit from 0.4.4 to 0.4.5
  • dtplyr from 1.3.1 to 1.3.2
  • evaluate from 1.0.3 to 1.0.5
  • fansi from 1.0.6 to 1.0.7
  • forcats from 1.0.0 to 1.0.1
  • fs from 1.6.5 to 1.6.6
  • future from 1.34.0 to 1.68.0
  • future.apply from 1.11.3 to 1.20.0
  • gargle from 1.5.2 to 1.6.0
  • gert from 2.1.4 to 2.2.0
  • ggplot2 from 3.5.1 to 4.0.1
  • gh from 1.4.1 to 1.5.0
  • git2r from 0.35.0 to 0.36.2
  • glmnet from 4.1-8 to 4.1-10
  • googledrive from 2.1.1 to 2.1.2
  • googlesheets4 from 1.1.1 to 1.1.2
  • graphics from 4.4.2 to 4.5.1
  • grDevices from 4.4.2 to 4.5.1
  • grid from 4.4.2 to 4.5.1
  • gt from 0.11.1 to 1.1.0
  • hardhat from 1.4.1 to 1.4.2
  • haven from 2.5.4 to 2.5.5
  • hms from 1.1.3 to 1.1.4
  • httpuv from 1.6.15 to 1.6.16
  • httr2 from 1.1.1 to 1.2.1
  • jsonlite from 1.9.1 to 2.0.0
  • later from 1.4.1 to 1.4.4
  • lava from 1.8.1 to 1.8.2
  • listenv from 0.9.1 to 0.10.0
  • magrittr from 2.0.3 to 2.0.4
  • markdown from 1.13 to 2.0
  • methods from 4.4.2 to 4.5.1
  • miniUI from 0.1.1.1 to 0.1.2
  • mlflow from 2.20.4 to 3.6.0
  • openssl from 2.3.3 to 2.3.4
  • parallel from 4.4.2 to 4.5.1
  • parallelly from 1.42.0 to 1.45.1
  • pillar from 1.11.0 to 1.11.1
  • pkgbuild from 1.4.6 to 1.4.8
  • pkgdown from 2.1.1 to 2.2.0
  • pkgload from 1.4.0 to 1.4.1
  • pROC from 1.18.5 to 1.19.0.1
  • prodlim from 2024.06.25 to 2025.04.28
  • progressr from 0.15.1 to 0.18.0
  • promises from 1.3.2 to 1.5.0
  • ps from 1.9.0 to 1.9.1
  • purrr from 1.0.4 to 1.2.0
  • ragg from 1.3.3 to 1.5.0
  • Rcpp from 1.0.14 to 1.1.0
  • readr from 2.1.5 to 2.1.6
  • recipes from 1.2.0 to 1.3.1
  • reshape2 from 1.4.4 to 1.4.5
  • rmarkdown from 2.29 to 2.30
  • roxygen2 from 7.3.2 to 7.3.3
  • rprojroot from 2.0.4 to 2.1.1
  • RSQLite from 2.3.9 to 2.4.4
  • rversions from 2.1.2 to 3.0.0
  • rvest from 1.0.4 to 1.0.5
  • sass from 0.4.9 to 0.4.10
  • scales from 1.3.0 to 1.4.0
  • shiny from 1.10.0 to 1.11.1
  • sparklyr from 1.9.1 to 1.9.3
  • SparkR from 4.0.0 to 4.1.0
  • sparsevctrs from 0.3.1 to 0.3.4
  • splines from 4.4.2 to 4.5.1
  • stats from 4.4.2 to 4.5.1
  • stats4 from 4.4.2 to 4.5.1
  • stringr from 1.5.1 to 1.6.0
  • systemfonts from 1.2.1 to 1.3.1
  • tcltk from 4.4.2 to 4.5.1
  • testthat from 3.2.3 to 3.3.0
  • textshaping from 1.0.0 to 1.0.4
  • timeDate from 4041.110 to 4051.111
  • tinytex from 0.56 to 0.58
  • tools from 4.4.2 to 4.5.1
  • usethis from 3.1.0 to 3.2.1
  • utils from 4.4.2 to 4.5.1
  • V8 from 6.0.2 to 8.0.1
  • vroom from 1.6.5 to 1.6.6
  • waldo from 0.6.1 to 0.6.2
  • xfun from 0.51 to 0.54
  • xml2 from 1.3.8 to 1.5.0
  • zeallot from 0.1.0 to 0.2.0
  • zip from 2.3.2 to 2.3.3

• Upgraded Java libraries:

  • com.amazonaws.amazon-kinesis-client from 1.12.0 to 1.15.3
  • com.amazonaws.aws-java-sdk-autoscaling from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-cloudformation from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-cloudfront from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-cloudhsm from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-cloudsearch from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-cloudtrail from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-cloudwatch from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-cloudwatchmetrics from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-codedeploy from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-cognitoidentity from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-cognitosync from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-config from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-core from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-datapipeline from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-directconnect from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-directory from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-dynamodb from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-ec2 from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-ecs from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-efs from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-elasticache from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-elasticbeanstalk from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-elasticloadbalancing from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-elastictranscoder from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-emr from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-glacier from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-glue from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-iam from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-importexport from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-kinesis from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-kms from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-lambda from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-logs from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-machinelearning from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-opsworks from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-rds from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-redshift from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-route53 from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-s3 from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-ses from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-simpledb from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-simpleworkflow from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-sns from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-sqs from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-ssm from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-storagegateway from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-sts from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-support from 1.12.638 to 1.12.681
  • com.amazonaws.aws-java-sdk-workspaces from 1.12.638 to 1.12.681
  • com.amazonaws.jmespath-java from 1.12.638 to 1.12.681
  • com.databricks.databricks-sdk-java from 0.27.0 to 0.53.0
  • com.fasterxml.jackson.datatype.jackson-datatype-jsr310 from 2.18.2 to 2.18.3
  • com.github.luben.zstd-jni from 1.5.6-10 to 1.5.7-6
  • com.google.flatbuffers.flatbuffers-java from 24.3.25 to 25.2.10
  • com.google.guava.failureaccess from 1.0.2 to 1.0.3
  • com.google.guava.guava from 33.4.0-jre to 33.4.8-jre
  • com.microsoft.sqlserver.mssql-jdbc from 11.2.3.jre8 to 12.8.0.jre8
  • commons-cli.commons-cli from 1.9.0 to 1.10.0
  • commons-codec.commons-codec from 1.17.2 to 1.19.0
  • commons-fileupload.commons-fileupload from 1.5 to 1.6.0
  • commons-io.commons-io from 2.18.0 to 2.21.0
  • dev.ludovic.netlib.arpack from 3.0.3 to 3.0.4
  • dev.ludovic.netlib.blas from 3.0.3 to 3.0.4
  • dev.ludovic.netlib.lapack from 3.0.3 to 3.0.4
  • io.dropwizard.metrics.metrics-annotation from 4.2.30 to 4.2.37
  • io.dropwizard.metrics.metrics-core from 4.2.30 to 4.2.37
  • io.dropwizard.metrics.metrics-graphite from 4.2.30 to 4.2.37
  • io.dropwizard.metrics.metrics-healthchecks from 4.2.30 to 4.2.37
  • io.dropwizard.metrics.metrics-jmx from 4.2.30 to 4.2.37
  • io.dropwizard.metrics.metrics-json from 4.2.30 to 4.2.37
  • io.dropwizard.metrics.metrics-jvm from 4.2.30 to 4.2.37
  • io.dropwizard.metrics.metrics-servlets from 4.2.30 to 4.2.37
  • io.delta.delta-sharing-client_2.13 from 1.3.10 to 1.3.11
  • io.netty.netty-all from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-buffer from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-codec from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-codec-http from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-codec-http2 from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-codec-socks from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-common from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-handler from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-handler-proxy from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-resolver from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-tcnative-boringssl-static from 2.0.70.Final-db-r0-windows-x86_64 to 2.0.74.Final-db-r0-windows-x86_64
  • io.netty.netty-tcnative-classes from 2.0.70.Final to 2.0.74.Final
  • io.netty.netty-transport from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-transport-classes-epoll from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-transport-classes-kqueue from 4.1.118.Final to 4.2.7.Final
  • io.netty.netty-transport-native-epoll from 4.1.118.Final-linux-x86_64 to 4.2.7.Final-linux-x86_64
  • io.netty.netty-transport-native-kqueue from 4.1.118.Final-osx-x86_64 to 4.2.7.Final-osx-x86_64
  • io.netty.netty-transport-native-unix-common from 4.1.118.Final to 4.2.7.Final
  • joda-time.joda-time from 2.13.0 to 2.14.0
  • org.apache.arrow.arrow-format from 18.2.0 to 18.3.0
  • org.apache.arrow.arrow-memory-core from 18.2.0 to 18.3.0
  • org.apache.arrow.arrow-memory-netty from 18.2.0 to 18.3.0
  • org.apache.arrow.arrow-memory-netty-buffer-patch from 18.2.0 to 18.3.0
  • org.apache.arrow.arrow-vector from 18.2.0 to 18.3.0
  • org.apache.avro.avro from 1.12.0 to 1.12.1
  • org.apache.avro.avro-ipc from 1.12.0 to 1.12.1
  • org.apache.avro.avro-mapred from 1.12.0 to 1.12.1
  • org.apache.commons.commons-collections4 from 4.4 to 4.5.0
  • org.apache.commons.commons-compress from 1.27.1 to 1.28.0
  • org.apache.commons.commons-lang3 from 3.17.0 to 3.19.0
  • org.apache.commons.commons-text from 1.13.0 to 1.14.0
  • org.apache.curator.curator-client from 5.7.1 to 5.9.0
  • org.apache.curator.curator-framework from 5.7.1 to 5.9.0
  • org.apache.curator.curator-recipes from 5.7.1 to 5.9.0
  • org.apache.datasketches.datasketches-java from 6.1.1 to 6.2.0
  • org.apache.hadoop.hadoop-client-runtime from 3.4.1 to 3.4.2
  • org.apache.orc.orc-core from 2.1.1-shaded-protobuf to 2.2.0-shaded-protobuf
  • org.apache.orc.orc-format from 1.1.0-shaded-protobuf to 1.1.1-shaded-protobuf
  • org.apache.orc.orc-mapreduce from 2.1.1-shaded-protobuf to 2.2.0-shaded-protobuf
  • org.apache.orc.orc-shims from 2.1.1 to 2.2.0
  • org.apache.xbean.xbean-asm9-shaded from 4.26 to 4.28
  • org.apache.zookeeper.zookeeper from 3.9.3 to 3.9.4
  • org.apache.zookeeper.zookeeper-jute from 3.9.3 to 3.9.4
  • org.eclipse.jetty.jetty-client from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-http from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-io from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-jndi from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-plus from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-proxy from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-security from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-server from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-servlet from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-servlets from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-util from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-webapp from 9.4.53.v20231009 to 10.0.26
  • org.eclipse.jetty.jetty-xml from 9.4.53.v20231009 to 10.0.26
  • org.mlflow.mlflow-spark_2.13 from 2.9.1 to 2.22.1
  • org.objenesis.objenesis from 3.3 to 3.4
  • org.scala-lang.modules.scala-xml_2.13 from 2.3.0 to 2.4.0

Databricks ODBC/JDBC driver support

Databricks supports ODBC/JDBC drivers released in the past 2 years. Please download the recently released drivers and upgrade (download ODBC, download JDBC).

System environment

• Operating System: Ubuntu 24.04.4 LTS
• Java: Zulu21.42+19-CA
• Scala: 2.13.16
• Python: 3.12.3
• R: 4.5.1
• Delta Lake: 4.2.0

Installed Python libraries

Library	Version	Library	Version	Library	Version
aiohappyeyeballs	2.4.4	aiohttp	3.11.10	aiosignal	1.2.0
annotated-doc	0.0.4	annotated-types	0.7.0	anyio	4.7.0
argon2-cffi	21.3.0	argon2-cffi-bindings	21.2.0	arro3-core	0.6.5
arrow	1.3.0	asttokens	3.0.0	astunparse	1.6.3
async-lru	2.0.4	attrs	24.3.0	autocommand	2.2.2
azure-common	1.1.28	azure-core	1.37.0	azure-identity	1.20.0
azure-mgmt-core	1.6.0	azure-mgmt-web	8.0.0	azure-storage-blob	12.28.0
azure-storage-file-datalake	12.22.0	babel	2.16.0	backports.tarfile	1.2.0
beautifulsoup4	4.12.3	black	24.10.0	bleach	6.2.0
blinker	1.7.0	boto3	1.40.45	botocore	1.40.45
cachetools	5.5.1	certifi	2025.4.26	cffi	1.17.1
chardet	4.0.0	charset-normalizer	3.3.2	click	8.1.8
cloudpickle	3.0.0	comm	0.2.1	contourpy	1.3.1
cryptography	44.0.1	cycler	0.11.0	Cython	3.1.5
databricks-agents	1.9.1	databricks-sdk	0.67.0	dataclasses-json	0.6.7
dbus-python	1.3.2	debugpy	1.8.11	decorator	5.1.1
defusedxml	0.7.1	deltalake	1.1.4	Deprecated	1.2.18
distlib	0.3.9	docstring-to-markdown	0.11	executing	1.2.0
facets-overview	1.1.1	fastapi	0.128.0	fastjsonschema	2.21.1
filelock	3.17.0	fonttools	4.55.3	fqdn	1.5.1
frozenlist	1.5.0	fsspec	2023.5.0	gitdb	4.0.11
GitPython	3.1.43	google-api-core	2.28.1	google-auth	2.47.0
google-cloud-core	2.5.0	google-cloud-storage	3.7.0	google-crc32c	1.8.0
google-resumable-media	2.8.0	googleapis-common-protos	1.65.0	grpcio	1.67.0
grpcio-status	1.67.0	h11	0.16.0	hf-xet	1.2.0
httpcore	1.0.9	httplib2	0.20.4	httpx	0.28.1
huggingface_hub	1.2.4	idna	3.7	importlib_metadata	8.5.0
inflect	7.3.1	iniconfig	1.1.1	ipyflow-core	0.0.209
ipykernel	6.29.5	ipython	8.30.0	ipython-genutils	0.2.0
ipywidgets	7.8.1	isodate	0.7.2	isoduration	20.11.0
jaraco.collections	5.1.0	jaraco.context	5.3.0	jaraco.functools	4.0.1
jaraco.text	3.12.1	jedi	0.19.2	Jinja2	3.1.6
jiter	0.12.0	jmespath	1.0.1	joblib	1.4.2
json5	0.9.25	jsonpatch	1.33	jsonpointer	3.0.0
jsonschema	4.23.0	jsonschema-specifications	2023.7.1	jupyter-events	0.12.0
jupyter-lsp	2.2.5	jupyter_client	8.6.3	jupyter_core	5.7.2
jupyter_server	2.15.0	jupyter_server_terminals	0.5.3	jupyterlab	4.3.4
jupyterlab_pygments	0.3.0	jupyterlab_server	2.27.3	jupyterlab_widgets	1.1.11
kiwisolver	1.4.8	langchain-core	1.2.6	langchain-openai	1.1.6
langsmith	0.6.1	launchpadlib	1.11.0	lazr.restfulclient	0.14.6
lazr.uri	1.0.6	litellm	1.75.9	markdown-it-py	2.2.0
MarkupSafe	3.0.2	marshmallow	3.26.2	matplotlib	3.10.0
matplotlib-inline	0.1.7	mccabe	0.7.0	mdurl	0.1.0
mistune	3.1.2	mlflow-skinny	3.8.1	mmh3	5.2.0
more-itertools	10.3.0	msal	1.34.0	msal-extensions	1.3.1
multidict	6.1.0	mypy-extensions	1.0.0	nbclient	0.10.2
nbconvert	7.16.6	nbformat	5.10.4	nest-asyncio	1.6.0
nodeenv	1.10.0	notebook	7.3.2	notebook_shim	0.2.4
numpy	2.1.3	oauthlib	3.2.2	openai	2.14.0
opentelemetry-api	1.39.1	opentelemetry-proto	1.39.1	opentelemetry-sdk	1.39.1
opentelemetry-semantic-conventions	0.60b1	orjson	3.11.5	overrides	7.4.0
packaging	24.2	pandas	2.2.3	pandocfilters	1.5.0
parso	0.8.4	pathspec	0.10.3	patsy	1.0.1
pexpect	4.8.0	pillow	11.1.0	pip	25.0.1
platformdirs	4.3.7	plotly	5.24.1	pluggy	1.5.0
prometheus_client	0.21.1	prompt-toolkit	3.0.43	propcache	0.3.1
proto-plus	1.27.0	protobuf	5.29.4	psutil	5.9.0
psycopg2	2.9.11	ptyprocess	0.7.0	pure-eval	0.2.2
pyarrow	21.0.0	pyasn1	0.4.8	pyasn1-modules	0.2.8
pyccolo	0.0.71	pycparser	2.21	pydantic	2.10.6
pydantic_core	2.27.2	pyflakes	3.2.0	Pygments	2.19.1
PyGObject	3.48.2	pyiceberg	0.10.0	PyJWT	2.10.1
pyodbc	5.2.0	pyparsing	3.2.0	pyright	1.1.394
pyroaring	1.0.3	pytest	8.3.5	python-dateutil	2.9.0.post0
python-dotenv	1.2.1	python-json-logger	3.2.1	python-lsp-jsonrpc	1.1.2
python-lsp-server	1.12.2	pytoolconfig	1.2.6	pytz	2024.1
PyYAML	6.0.2	pyzmq	26.2.0	referencing	0.30.2
regex	2024.11.6	requests	2.32.3	requests-toolbelt	1.0.0
rfc3339-validator	0.1.4	rfc3986-validator	0.1.1	rich	13.9.4
rope	1.13.0	rpds-py	0.22.3	rsa	4.9.1
s3transfer	0.14.0	scikit-learn	1.6.1	scipy	1.15.3
seaborn	0.13.2	Send2Trash	1.8.2	setuptools	78.1.1
shellingham	1.5.4	six	1.17.0	smmap	5.0.0
sniffio	1.3.0	sortedcontainers	2.4.0	soupsieve	2.5
sqlparse	0.5.5	ssh-import-id	5.11	stack-data	0.6.3
starlette	0.50.0	strictyaml	1.7.3	tenacity	9.0.0
terminado	0.17.1	threadpoolctl	3.5.0	tiktoken	0.12.0
tinycss2	1.4.0	tokenize_rt	6.1.0	tokenizers	0.22.2
tomli	2.0.1	tornado	6.5.1	tqdm	4.67.1
traitlets	5.14.3	typeguard	4.3.0	typer-slim	0.21.1
types-python-dateutil	2.9.0.20251115	typing-inspect	0.9.0	typing_extensions	4.12.2
tzdata	2024.1	ujson	5.10.0	unattended-upgrades	0.1
uri-template	1.3.0	urllib3	2.3.0	uuid_utils	0.12.0
uvicorn	0.40.0	virtualenv	20.29.3	wadllib	1.3.6
wcwidth	0.2.5	webcolors	25.10.0	webencodings	0.5.1
websocket-client	1.8.0	whatthepatch	1.0.2	wheel	0.45.1
whenever	0.7.3	widgetsnbextension	3.6.6	wrapt	1.17.0
yapf	0.40.2	yarl	1.18.0	zipp	3.21.0
zstandard	0.23.0

Installed R libraries

R libraries are installed from the Posit Package Manager CRAN snapshot on PACKAGES.

Library	Version	Library	Version	Library	Version
arrow	22.0.0	askpass	1.2.1	assertthat	0.2.1
backports	1.5.0	base	4.5.1	base64enc	0.1-3
bigD	0.3.1	bit	4.6.0	bit64	4.6.0-1
bitops	1.0-9	blob	1.2.4	boot	1.3-30
brew	1.0-10	brio	1.1.5	broom	1.0.10
bslib	0.9.0	cachem	1.1.0	callr	3.7.6
caret	7.0-1	cellranger	1.1.0	chron	2.3-62
class	7.3-22	cli	3.6.5	clipr	0.8.0
clock	0.7.3	cluster	2.1.6	codetools	0.2-20
commonmark	2.0.0	compiler	4.5.1	config	0.3.2
conflicted	1.2.0	cpp11	0.5.2	crayon	1.5.3
credentials	2.0.3	curl	7.0.0	data.table	1.17.8
datasets	4.5.1	DBI	1.2.3	dbplyr	2.5.1
desc	1.4.3	devtools	2.4.6	diagram	1.6.5
diffobj	0.3.6	digest	0.6.39	downlit	0.4.5
dplyr	1.1.4	dtplyr	1.3.2	e1071	1.7-16
ellipsis	0.3.2	evaluate	1.0.5	fansi	1.0.7
farver	2.1.2	fastmap	1.2.0	fontawesome	0.5.3
forcats	1.0.1	foreach	1.5.2	foreign	0.8-86
fs	1.6.6	future	1.68.0	future.apply	1.20.0
gargle	1.6.0	generics	0.1.4	gert	2.2.0
ggplot2	4.0.1	gh	1.5.0	git2r	0.36.2
gitcreds	0.1.2	glmnet	4.1-10	globals	0.18.0
glue	1.8.0	googledrive	2.1.2	googlesheets4	1.1.2
gower	1.0.2	graphics	4.5.1	grDevices	4.5.1
grid	4.5.1	gridExtra	2.3	gsubfn	0.7
gt	1.1.0	gtable	0.3.6	hardhat	1.4.2
haven	2.5.5	highr	0.11	hms	1.1.4
htmltools	0.5.8.1	htmlwidgets	1.6.4	httpuv	1.6.16
httr	1.4.7	httr2	1.2.1	ids	1.0.1
ini	0.3.1	ipred	0.9-15	isoband	0.2.7
iterators	1.0.14	jquerylib	0.1.4	jsonlite	2.0.0
juicyjuice	0.1.0	KernSmooth	2.23-22	knitr	1.50
labeling	0.4.3	later	1.4.4	lattice	0.22-5
lava	1.8.2	lifecycle	1.0.4	listenv	0.10.0
litedown	0.8	lubridate	1.9.4	magrittr	2.0.4
markdown	2.0	MASS	7.3-60.0.1	Matrix	1.6-5
memoise	2.0.1	methods	4.5.1	mgcv	1.9-1
mime	0.13	miniUI	0.1.2	mlflow	3.6.0
ModelMetrics	1.2.2.2	modelr	0.1.11	nlme	3.1-164
nnet	7.3-19	numDeriv	2016.8-1.1	openssl	2.3.4
otel	0.2.0	parallel	4.5.1	parallelly	1.45.1
pillar	1.11.1	pkgbuild	1.4.8	pkgconfig	2.0.3
pkgdown	2.2.0	pkgload	1.4.1	plogr	0.2.0
plyr	1.8.9	praise	1.0.0	prettyunits	1.2.0
pROC	1.19.0.1	processx	3.8.6	prodlim	2025.04.28
profvis	0.4.0	progress	1.2.3	progressr	0.18.0
promises	1.5.0	proto	1.0.0	proxy	0.4-27
ps	1.9.1	purrr	1.2.0	R6	2.6.1
ragg	1.5.0	randomForest	4.7-1.2	rappdirs	0.3.3
rcmdcheck	1.4.0	RColorBrewer	1.1-3	Rcpp	1.1.0
RcppEigen	0.3.4.0.2	reactable	0.4.4	reactR	0.6.1
readr	2.1.6	readxl	1.4.5	recipes	1.3.1
rematch	2.0.0	rematch2	2.1.2	remotes	2.5.0
reprex	2.1.1	reshape2	1.4.5	rlang	1.1.6
rmarkdown	2.30	RODBC	1.3-26	roxygen2	7.3.3
rpart	4.1.23	rprojroot	2.1.1	Rserve	1.8-15
RSQLite	2.4.4	rstudioapi	0.17.1	rversions	3.0.0
rvest	1.0.5	S7	0.2.1	sass	0.4.10
scales	1.4.0	selectr	0.4-2	sessioninfo	1.2.3
shape	1.4.6.1	shiny	1.11.1	sourcetools	0.1.7-1
sparklyr	1.9.3	SparkR	4.1.0	sparsevctrs	0.3.4
spatial	7.3-17	splines	4.5.1	sqldf	0.4-11
SQUAREM	2021.1	stats	4.5.1	stats4	4.5.1
stringi	1.8.7	stringr	1.6.0	survival	3.5-8
swagger	5.17.14.1	sys	3.4.3	systemfonts	1.3.1
tcltk	4.5.1	testthat	3.3.0	textshaping	1.0.4
tibble	3.3.0	tidyr	1.3.1	tidyselect	1.2.1
tidyverse	2.0.0	timechange	0.3.0	timeDate	4051.111
tinytex	0.58	tools	4.5.1	tzdb	0.5.0
urlchecker	1.0.1	usethis	3.2.1	utf8	1.2.6
utils	4.5.1	uuid	1.2-1	V8	8.0.1
vctrs	0.6.5	viridisLite	0.4.2	vroom	1.6.6
waldo	0.6.2	whisker	0.4.1	withr	3.0.2
xfun	0.54	xml2	1.5.0	xopen	1.0.1
xtable	1.8-4	yaml	2.3.10	zeallot	0.2.0
zip	2.3.3

Installed Java and Scala libraries (Scala 2.13 cluster version)

Group ID	Artifact ID	Version
antlr	antlr	2.7.7
com.clearspring.analytics	stream	2.9.8
com.databricks	Rserve	1.8-3
com.databricks	databricks-sdk-java	0.53.0
com.databricks	jets3t	0.7.1-0
com.databricks.scalapb	scalapb-runtime_2.13	0.4.15-11
com.esotericsoftware	kryo-shaded	4.0.3
com.esotericsoftware	minlog	1.3.0
com.fasterxml	classmate	1.5.1
com.fasterxml.jackson.core	jackson-annotations	2.18.2
com.fasterxml.jackson.core	jackson-core	2.18.2
com.fasterxml.jackson.core	jackson-databind	2.18.2
com.fasterxml.jackson.dataformat	jackson-dataformat-yaml	2.15.2
com.fasterxml.jackson.datatype	jackson-datatype-joda	2.18.2
com.fasterxml.jackson.datatype	jackson-datatype-jsr310	2.18.3
com.fasterxml.jackson.module	jackson-module-paranamer	2.18.2
com.fasterxml.jackson.module	jackson-module-scala_2.13	2.18.2
com.github.ben-manes.caffeine	caffeine	2.9.3
com.github.blemale	scaffeine_2.13	4.1.0
com.github.fommil	jniloader	1.1
com.github.fommil.netlib	native_ref-java	1.1
com.github.fommil.netlib	native_ref-java	1.1-natives
com.github.fommil.netlib	native_system-java	1.1
com.github.fommil.netlib	native_system-java	1.1-natives
com.github.fommil.netlib	netlib-native_ref-linux-x86_64	1.1-natives
com.github.fommil.netlib	netlib-native_system-linux-x86_64	1.1-natives
com.github.luben	zstd-jni	1.5.7-6
com.github.virtuald	curvesapi	1.08
com.github.wendykierp	JTransforms	3.1
com.google.api.grpc	proto-google-common-protos	2.5.1
com.google.auth	google-auth-library-credentials	1.20.0
com.google.auth	google-auth-library-oauth2-http	1.20.0
com.google.auto.value	auto-value-annotations	1.10.4
com.google.code.findbugs	jsr305	3.0.0
com.google.code.gson	gson	2.11.0
com.google.crypto.tink	tink	1.16.0
com.google.errorprone	error_prone_annotations	2.36.0
com.google.flatbuffers	flatbuffers-java	25.2.10
com.google.guava	failureaccess	1.0.3
com.google.guava	guava	33.4.8-jre
com.google.http-client	google-http-client	1.43.3
com.google.http-client	google-http-client-gson	1.43.3
com.google.j2objc	j2objc-annotations	3.0.0
com.google.protobuf	protobuf-java	3.25.5
com.google.protobuf	protobuf-java-util	3.25.5
com.helger	profiler	1.1.1
com.ibm.icu	icu4j	75.1
com.jcraft	jsch	0.1.55
com.lihaoyi	sourcecode_2.13	0.1.9
com.microsoft.azure	azure-data-lake-store-sdk	2.3.10
com.microsoft.sqlserver	mssql-jdbc	12.8.0.jre11
com.microsoft.sqlserver	mssql-jdbc	12.8.0.jre8
com.ning	compress-lzf	1.1.2
com.sun.mail	javax.mail	1.5.2
com.sun.xml.bind	jaxb-core	2.2.11
com.sun.xml.bind	jaxb-impl	2.2.11
com.tdunning	json	1.8
com.thoughtworks.paranamer	paranamer	2.8
com.trueaccord.lenses	lenses_2.13	0.4.13
com.twitter	chill-java	0.10.0
com.twitter	chill_2.13	0.10.0
com.twitter	util-app_2.13	19.8.1
com.twitter	util-core_2.13	19.8.1
com.twitter	util-function_2.13	19.8.1
com.twitter	util-jvm_2.13	19.8.1
com.twitter	util-lint_2.13	19.8.1
com.twitter	util-registry_2.13	19.8.1
com.twitter	util-stats_2.13	19.8.1
com.typesafe	config	1.4.3
com.typesafe.scala-logging	scala-logging_2.13	3.9.2
com.uber	h3	3.7.3
com.univocity	univocity-parsers	2.9.1
com.zaxxer	HikariCP	4.0.3
com.zaxxer	SparseBitSet	1.3
commons-cli	commons-cli	1.10.0
commons-codec	commons-codec	1.19.0
commons-collections	commons-collections	3.2.2
commons-dbcp	commons-dbcp	1.4
commons-fileupload	commons-fileupload	1.6.0
commons-httpclient	commons-httpclient	3.1
commons-io	commons-io	2.21.0
commons-lang	commons-lang	2.6
commons-logging	commons-logging	1.1.3
commons-pool	commons-pool	1.5.4
dev.ludovic.netlib	arpack	3.0.4
dev.ludovic.netlib	blas	3.0.4
dev.ludovic.netlib	lapack	3.0.4
info.ganglia.gmetric4j	gmetric4j	1.0.10
io.airlift	aircompressor	2.0.2
io.delta	delta-sharing-client_2.13	1.3.11
io.dropwizard.metrics	metrics-annotation	4.2.37
io.dropwizard.metrics	metrics-core	4.2.37
io.dropwizard.metrics	metrics-graphite	4.2.37
io.dropwizard.metrics	metrics-healthchecks	4.2.37
io.dropwizard.metrics	metrics-jetty10	4.2.37
io.dropwizard.metrics	metrics-jmx	4.2.37
io.dropwizard.metrics	metrics-json	4.2.37
io.dropwizard.metrics	metrics-jvm	4.2.37
io.dropwizard.metrics	metrics-servlets	4.2.37
io.github.java-diff-utils	java-diff-utils	4.15
io.netty	netty-all	4.2.7.Final
io.netty	netty-buffer	4.2.7.Final
io.netty	netty-codec	4.2.7.Final
io.netty	netty-codec-base	4.2.7.Final
io.netty	netty-codec-classes-quic	4.2.7.Final
io.netty	netty-codec-compression	4.2.7.Final
io.netty	netty-codec-http	4.2.7.Final
io.netty	netty-codec-http2	4.2.7.Final
io.netty	netty-codec-http3	4.2.7.Final
io.netty	netty-codec-marshalling	4.2.7.Final
io.netty	netty-codec-native-quic	4.2.7.Final-linux-aarch_64
io.netty	netty-codec-native-quic	4.2.7.Final-linux-x86_64
io.netty	netty-codec-native-quic	4.2.7.Final-osx-aarch_64
io.netty	netty-codec-native-quic	4.2.7.Final-osx-x86_64
io.netty	netty-codec-native-quic	4.2.7.Final-windows-x86_64
io.netty	netty-codec-protobuf	4.2.7.Final
io.netty	netty-codec-socks	4.2.7.Final
io.netty	netty-common	4.2.7.Final
io.netty	netty-handler	4.2.7.Final
io.netty	netty-handler-proxy	4.2.7.Final
io.netty	netty-resolver	4.2.7.Final
io.netty	netty-tcnative-boringssl-static	2.0.74.Final-db-r0-linux-aarch_64
io.netty	netty-tcnative-boringssl-static	2.0.74.Final-db-r0-linux-x86_64
io.netty	netty-tcnative-boringssl-static	2.0.74.Final-db-r0-osx-aarch_64
io.netty	netty-tcnative-boringssl-static	2.0.74.Final-db-r0-osx-x86_64
io.netty	netty-tcnative-boringssl-static	2.0.74.Final-db-r0-windows-x86_64
io.netty	netty-tcnative-classes	2.0.74.Final
io.netty	netty-transport	4.2.7.Final
io.netty	netty-transport-classes-epoll	4.2.7.Final
io.netty	netty-transport-classes-io_uring	4.2.7.Final
io.netty	netty-transport-classes-kqueue	4.2.7.Final
io.netty	netty-transport-native-epoll	4.2.7.Final
io.netty	netty-transport-native-epoll	4.2.7.Final-linux-aarch_64
io.netty	netty-transport-native-epoll	4.2.7.Final-linux-riscv64
io.netty	netty-transport-native-epoll	4.2.7.Final-linux-x86_64
io.netty	netty-transport-native-io_uring	4.2.7.Final-linux-aarch_64
io.netty	netty-transport-native-io_uring	4.2.7.Final-linux-riscv64
io.netty	netty-transport-native-io_uring	4.2.7.Final-linux-x86_64
io.netty	netty-transport-native-kqueue	4.2.7.Final-osx-aarch_64
io.netty	netty-transport-native-kqueue	4.2.7.Final-osx-x86_64
io.netty	netty-transport-native-unix-common	4.2.7.Final
io.opencensus	opencensus-api	0.31.1
io.opencensus	opencensus-contrib-http-util	0.31.1
io.prometheus	simpleclient	0.16.1-databricks
io.prometheus	simpleclient_common	0.16.1-databricks
io.prometheus	simpleclient_dropwizard	0.16.1-databricks
io.prometheus	simpleclient_pushgateway	0.16.1-databricks
io.prometheus	simpleclient_servlet	0.16.1-databricks
io.prometheus	simpleclient_servlet_common	0.16.1-databricks
io.prometheus	simpleclient_tracer_common	0.16.1-databricks
io.prometheus	simpleclient_tracer_otel	0.16.1-databricks
io.prometheus	simpleclient_tracer_otel_agent	0.16.1-databricks
io.prometheus.jmx	collector	0.18.0
jakarta.annotation	jakarta.annotation-api	1.3.5
jakarta.servlet	jakarta.servlet-api	4.0.3
jakarta.validation	jakarta.validation-api	2.0.2
jakarta.ws.rs	jakarta.ws.rs-api	2.1.6
javax.activation	activation	1.1.1
javax.annotation	javax.annotation-api	1.3.2
javax.el	javax.el-api	2.2.4
javax.jdo	jdo-api	3.0.1
javax.transaction	jta	1.1
javax.transaction	transaction-api	1.1
javax.xml.bind	jaxb-api	2.2.11
javolution	javolution	5.5.1
jline	jline	2.14.6
joda-time	joda-time	2.14.0
net.java.dev.jna	jna	5.8.0
net.razorvine	pickle	1.5
net.sf.jpam	jpam	1.1
net.sf.opencsv	opencsv	2.3
net.sf.supercsv	super-csv	2.2.0
net.snowflake	snowflake-ingest-sdk	0.9.6
net.sourceforge.f2j	arpack_combined_all	0.1
org.acplt.remotetea	remotetea-oncrpc	1.1.2
org.antlr	ST4	4.0.4
org.antlr	antlr-runtime	3.5.2
org.antlr	antlr4-runtime	4.13.1
org.antlr	stringtemplate	3.2.1
org.apache.ant	ant	1.10.11
org.apache.ant	ant-jsch	1.10.11
org.apache.ant	ant-launcher	1.10.11
org.apache.arrow	arrow-compression	18.3.0
org.apache.arrow	arrow-format	18.3.0
org.apache.arrow	arrow-memory-core	18.3.0
org.apache.arrow	arrow-memory-netty	18.3.0
org.apache.arrow	arrow-memory-netty-buffer-patch	18.3.0
org.apache.arrow	arrow-vector	18.3.0
org.apache.avro	avro	1.12.1
org.apache.avro	avro-ipc	1.12.1
org.apache.avro	avro-mapred	1.12.1
org.apache.commons	commons-collections4	4.5.0
org.apache.commons	commons-compress	1.28.0
org.apache.commons	commons-configuration2	2.11.0
org.apache.commons	commons-crypto	1.1.0
org.apache.commons	commons-lang3	3.19.0
org.apache.commons	commons-math3	3.6.1
org.apache.commons	commons-text	1.14.0
org.apache.curator	curator-client	5.9.0
org.apache.curator	curator-framework	5.9.0
org.apache.curator	curator-recipes	5.9.0
org.apache.datasketches	datasketches-java	6.2.0
org.apache.datasketches	datasketches-memory	3.0.2
org.apache.derby	derby	10.14.2.0
org.apache.hadoop	hadoop-client-runtime	3.4.2
org.apache.hive	hive-beeline	2.3.10
org.apache.hive	hive-cli	2.3.10
org.apache.hive	hive-jdbc	2.3.10
org.apache.hive	hive-llap-client	2.3.10
org.apache.hive	hive-llap-common	2.3.10
org.apache.hive	hive-serde	2.3.10
org.apache.hive	hive-shims	2.3.10
org.apache.hive	hive-storage-api	2.8.1
org.apache.hive.shims	hive-shims-0.23	2.3.10
org.apache.hive.shims	hive-shims-common	2.3.10
org.apache.hive.shims	hive-shims-scheduler	2.3.10
org.apache.httpcomponents	httpclient	4.5.14
org.apache.httpcomponents	httpcore	4.4.16
org.apache.ivy	ivy	2.5.3
org.apache.logging.log4j	log4j-1.2-api	2.24.3
org.apache.logging.log4j	log4j-api	2.24.3
org.apache.logging.log4j	log4j-core	2.24.3
org.apache.logging.log4j	log4j-layout-template-json	2.24.3
org.apache.logging.log4j	log4j-slf4j2-impl	2.24.3
org.apache.orc	orc-core	2.2.0-shaded-protobuf
org.apache.orc	orc-format	1.1.1-shaded-protobuf
org.apache.orc	orc-mapreduce	2.2.0-shaded-protobuf
org.apache.orc	orc-shims	2.2.0
org.apache.poi	poi	5.4.1
org.apache.poi	poi-ooxml	5.4.1
org.apache.poi	poi-ooxml-full	5.4.1
org.apache.poi	poi-ooxml-lite	5.4.1
org.apache.thrift	libfb303	0.9.3
org.apache.thrift	libthrift	0.16.0
org.apache.ws.xmlschema	xmlschema-core	2.3.1
org.apache.xbean	xbean-asm9-shaded	4.28
org.apache.xmlbeans	xmlbeans	5.3.0
org.apache.yetus	audience-annotations	0.13.0
org.apache.zookeeper	zookeeper	3.9.4
org.apache.zookeeper	zookeeper-jute	3.9.4
org.checkerframework	checker-qual	3.43.0
org.codehaus.janino	commons-compiler	3.0.16
org.codehaus.janino	janino	3.0.16
org.datanucleus	datanucleus-api-jdo	4.2.4
org.datanucleus	datanucleus-core	4.1.17
org.datanucleus	datanucleus-rdbms	4.1.19
org.datanucleus	javax.jdo	3.2.0-m3
org.eclipse.jetty	jetty-alpn-client	10.0.26
org.eclipse.jetty	jetty-client	10.0.26
org.eclipse.jetty	jetty-http	10.0.26
org.eclipse.jetty	jetty-io	10.0.26
org.eclipse.jetty	jetty-jndi	10.0.26
org.eclipse.jetty	jetty-plus	10.0.26
org.eclipse.jetty	jetty-proxy	10.0.26
org.eclipse.jetty	jetty-security	10.0.26
org.eclipse.jetty	jetty-server	10.0.26
org.eclipse.jetty	jetty-servlet	10.0.26
org.eclipse.jetty	jetty-servlets	10.0.26
org.eclipse.jetty	jetty-util	10.0.26
org.eclipse.jetty	jetty-webapp	10.0.26
org.eclipse.jetty	jetty-xml	10.0.26
org.fusesource.leveldbjni	leveldbjni-all	1.8
org.glassfish.hk2	hk2-api	2.6.1
org.glassfish.hk2	hk2-locator	2.6.1
org.glassfish.hk2	hk2-utils	2.6.1
org.glassfish.hk2	osgi-resource-locator	1.0.3
org.glassfish.hk2.external	aopalliance-repackaged	2.6.1
org.glassfish.hk2.external	jakarta.inject	2.6.1
org.glassfish.jersey.containers	jersey-container-servlet	2.41
org.glassfish.jersey.containers	jersey-container-servlet-core	2.41
org.glassfish.jersey.core	jersey-client	2.41
org.glassfish.jersey.core	jersey-common	2.41
org.glassfish.jersey.core	jersey-server	2.41
org.glassfish.jersey.inject	jersey-hk2	2.41
org.hibernate.validator	hibernate-validator	6.2.5.Final
org.ini4j	ini4j	0.5.4
org.javassist	javassist	3.29.2-GA
org.jboss.logging	jboss-logging	3.4.1.Final
org.jdbi	jdbi	2.63.1
org.jline	jline	3.27.1-jdk8
org.joda	joda-convert	1.7
org.json4s	json4s-ast_2.13	4.0.7
org.json4s	json4s-core_2.13	4.0.7
org.json4s	json4s-jackson-core_2.13	4.0.7
org.json4s	json4s-jackson_2.13	4.0.7
org.json4s	json4s-scalap_2.13	4.0.7
org.locationtech.jts	jts-core	1.20.0
org.lz4	lz4-java	1.8.0-databricks-1
org.mlflow	mlflow-spark_2.13	2.22.1
org.objenesis	objenesis	3.4
org.postgresql	postgresql	42.6.1
org.roaringbitmap	RoaringBitmap	1.2.1
org.rosuda.REngine	REngine	2.1.0
org.scala-lang	scala-compiler_2.13	2.13.16
org.scala-lang	scala-library_2.13	2.13.16
org.scala-lang	scala-reflect_2.13	2.13.16
org.scala-lang.modules	scala-collection-compat_2.13	2.11.0
org.scala-lang.modules	scala-java8-compat_2.13	0.9.1
org.scala-lang.modules	scala-parallel-collections_2.13	1.2.0
org.scala-lang.modules	scala-parser-combinators_2.13	2.4.0
org.scala-lang.modules	scala-xml_2.13	2.4.0
org.scala-sbt	test-interface	1.0
org.scalacheck	scalacheck_2.13	1.18.0
org.scalactic	scalactic_2.13	3.2.19
org.scalanlp	breeze-macros_2.13	2.1.0
org.scalanlp	breeze_2.13	2.1.0
org.scalatest	scalatest-compatible	3.2.19
org.scalatest	scalatest-core_2.13	3.2.19
org.scalatest	scalatest-diagrams_2.13	3.2.19
org.scalatest	scalatest-featurespec_2.13	3.2.19
org.scalatest	scalatest-flatspec_2.13	3.2.19
org.scalatest	scalatest-freespec_2.13	3.2.19
org.scalatest	scalatest-funspec_2.13	3.2.19
org.scalatest	scalatest-funsuite_2.13	3.2.19
org.scalatest	scalatest-matchers-core_2.13	3.2.19
org.scalatest	scalatest-mustmatchers_2.13	3.2.19
org.scalatest	scalatest-propspec_2.13	3.2.19
org.scalatest	scalatest-refspec_2.13	3.2.19
org.scalatest	scalatest-shouldmatchers_2.13	3.2.19
org.scalatest	scalatest-wordspec_2.13	3.2.19
org.scalatest	scalatest_2.13	3.2.19
org.slf4j	jcl-over-slf4j	2.0.16
org.slf4j	jul-to-slf4j	2.0.16
org.slf4j	slf4j-api	2.0.16
org.slf4j	slf4j-simple	1.7.25
org.threeten	threeten-extra	1.8.0
org.tukaani	xz	1.10
org.typelevel	algebra_2.13	2.8.0
org.typelevel	cats-kernel_2.13	2.8.0
org.typelevel	spire-macros_2.13	0.18.0
org.typelevel	spire-platform_2.13	0.18.0
org.typelevel	spire-util_2.13	0.18.0
org.typelevel	spire_2.13	0.18.0
org.wildfly.openssl	wildfly-openssl	1.1.3.Final
org.xerial	sqlite-jdbc	3.42.0.0
org.xerial.snappy	snappy-java	1.1.10.3
org.yaml	snakeyaml	2.0
oro	oro	2.0.8
pl.edu.icm	JLargeArrays	1.5
software.amazon.cryptools	AmazonCorrettoCryptoProvider	2.5.0-linux-x86_64
stax	stax-api	1.0.1