Databricks Runtime 4.1

Databricks released this image in May 2018.


This release was deprecated on January 17, 2019. For more information about the Databricks Runtime deprecation policy and schedule, see Databricks Runtime Versioning and Support Lifecycle.

The following release notes provide information about Databricks Runtime 4.1, powered by Apache Spark.

Delta Lake

Databricks Runtime version 4.1 adds major quality improvements and functionality to Delta Lake. Databricks highly recommends that all |Delta|customers upgrade to the new runtime. This release remains in Private Preview, but it represents a candidate release in anticipation of the upcoming general availability (GA) release.

Breaking changes

  • Databricks Runtime 4.1 includes changes to the transaction protocol to enable new features, such as validation. Tables created with Databricks Runtime 4.1 automatically use the new version and cannot be written to by older versions of Databricks Runtime. You must upgrade existing tables in order to take advantage of these improvements. To upgrade an existing table, first upgrade all jobs that are writing to the table. Then run:

    %scala"</path/to/table>" or "<tableName>")

    See Table Versioning for more information.

  • Writes are now validated against the current schema of the table rather than, as before, automatically adding columns that are missing from the destination table. To enable the previous behavior, set the mergeSchema option to true. See Schema validation.

  • If you are running earlier versions of Databricks Delta, you must upgrade all jobs before you use Databricks Runtime 4.1. If you see either of these errors, upgrade to Databricks Runtime 4.1:

    java.lang.NumberFormatException: For input string: "00000000000000....crc"
  • Tables can no longer have columns that differ only by case.

  • Delta-specific table configurations must now be prefixed with delta.

New features

  • Schema management - Databricks Delta now validates appends and overwrites to an existing table to ensure that the schema being written matches the schema.

    • Databricks Delta continues to support automatic schema migration.
    • Databricks Delta now supports the following DDL to modify schema explicitly:
      • ALTER TABLE ADD COLUMN to add new columns to a table
      • ALTER TABLE CHANGE COLUMNS to change column ordering

    For details, see Schema validation.

  • Enhanced DDL and table support

    • Full support for table DDL and saveAsTable(). save() and saveAsTable() now have identical semantics.
    • All DDL and DML commands support both table name and delta.`/path/to/table`.
    • Detailed table information - You can see the current reader and writer versions of a table by running DESCRIBE DETAIL. See Table Versioning.
    • Table details - Provenance information is now available for each write to a table. The Data sidebar also shows detailed table information and history for Databricks Delta tables. See Table metadata.
    • Streaming tables - Streaming DataFrames can be created using spark.readStream.format("delta").table("<table-name>").
    • Append-only tables - Databricks Delta now supports basic data governance. You can block deletes and modifications to a table by setting the table property delta.appendOnly=true.
    • MERGE INTO source - Adds more comprehensive support to the source query specification of MERGE. For example, you can specify LIMIT, ORDER BY and INLINE TABLE in the source.
    • Full support for Table ACLs.

Performance improvements

  • Reduced stats collection overhead - The efficiency of stats collection has been improved and stats are now only collected for a configurable number of columns, set to 32 by default. Databricks Delta write performance has been improved by up to 2x due to the reduction in stats collection overhead. To configure the number of columns, set the table property delta.dataSkippingNumIndexedCols=<number-of-columns>.
  • Support for limit push down - Statistics are used to limit the number of files scanned for queries that have LIMIT and predicates over partition columns. This is applicable to queries in notebooks due to the implicit limit=1000 in effect for all notebook commands.
  • Filter pushdown in the streaming source - Streaming queries now use partitioning when starting a new stream to skip irrelevant data.
  • Improved parallelism for OPTIMIZE - OPTIMIZE now runs as a single Spark task and will use all parallelism available on the cluster (previously was limited to 100 compacted files at a time).
  • Data Skipping in DML - UPDATE, DELETE, and MERGE now use statistics when locating files that need to be rewritten.
  • Randomized S3 prefixes - To avoid hot spots in S3 metadata for large tables, you can now set the table property delta.randomizeFilePrefixes=true.
  • Decreased checkpoint retention - checkpoints are now retained for two days (history is still retained for 30) to decrease storage costs for the transaction log.

API behavior

  • The behavior of insertInto(<table-name>) in Databricks Delta is the same as other data sources.
    • If no mode is specified or mode is ErrorIfExists, Ignore, or Append, appends the data in the DataFrame to the Databricks Delta table.
    • If mode is Overwrite, deletes all data in the existing table and inserts the data from the DataFrame into the Databricks Delta table.
  • If cached, the destination table of MERGE must be manually uncached.

Usability improvements

  • Workload migration validations - Common mistakes made when migrating workloads to Databricks Delta now throw an exception rather than failing:
    • Using format("parquet") to read or write a table.
    • Reading or writing directly to a partition (that is, /path/to/delta/part=1).
    • Vacuuming subdirectories of a table.
    • INSERT OVERWRITE DIRECTORY using Parquet on a table.
  • Case insensitive configuration - Options to the DataFrame Reader/Writer and table properties are now case insensitive (including both read path and write path).
  • Column names - Table column names can now include dots.

Known issues


Writes to a single table must originate from a single cluster. There is experimental support for writes from multiple clusters in the same workspace. Contact Databricks support if you are interested in trying this feature.

  • The inserts of multi-insert statements are in different units of work, rather than the same transaction.

Bug fixes

  • An infinite loop when starting a new stream on a fast updating table has been fixed.


Structured Streaming does not handle input that is not an append and throws an exception if any modifications occur on the table being used as a source. Previously you could override this behavior using the ignoreFileDeletion flag, but it is now deprecated. Instead use ignoreDeletes or ignoreChanges. See Delta Lake table as a stream source.

Other Changes and Improvements

  • Query Watchdog is enabled for all interactive clusters created using the UI.
  • Improved driver-side performance for the DBIO cache
  • Improved performance for Parquet decoding via a new native Parquet decoder
  • Improved performance for common subexpression elimination
  • Improved data skipping performance for large table joining small tables (fact-dimension table joins)
  • display() now renders columns containing image data types as rich HTML. See Images types in DataFrames.
  • New s3select data source for leveraging S3 Select
  • Improvements to Exporting and Importing ML Models
    • Upgraded dbml-local to latest release 0.4.1
    • Fixed bug with models exported with threshold parameter specified
    • Added support for exporting OneVsRestModel, GBTClassificationModel
  • Upgraded some installed Python libraries:
    • pip: from 9.0.1 to 10.0.0b2
    • setuptools: from 38.5.1 to 39.0.1
    • tornado: 4.5.3 to 5.0.1
    • wheel: 0.30.0 to 0.31.0
  • Upgraded several installed R libraries. See Installed R Libraries.
  • Upgraded AWS Java SDK from 1.11.253 to 1.11.313.
  • Upgraded Azure Data Lake Store SDK from 2.0.11 to 2.2.8.
  • Upgraded CUDA to 9.0 from 8.0 and CUDNN to 7.0 from 6.0 for GPU clusters.
  • For GPU clusters, GPU metrics now appear in the Cluster metrics Ganglia UI.

Apache Spark

Databricks Runtime 4.1 includes Apache Spark 2.3.0. This release includes all fixes and improvements included in Databricks Runtime 4.0, as well as the following additional bug fixes and improvements made to Spark:

  • [SPARK-24007][SQL] EqualNullSafe for FloatType and DoubleType might generate a wrong result by codegen.
  • [SPARK-23942][PYTHON][SQL] Makes collect in PySpark as action for a query executor listener
  • [SPARK-23815][CORE] Spark writer dynamic partition overwrite mode may fail to write output on multi level partition
  • [SPARK-23748][SS] Fix SS continuous process doesn’t support SubqueryAlias issue
  • [SPARK-23963][SQL] Properly handle large number of columns in query on text-based Hive table
  • [SPARK-23867][SCHEDULER] use droppedCount in logWarning
  • [SPARK-23816][CORE] Killed tasks should ignore FetchFailures.
  • [SPARK-23809][SQL] Active SparkSession should be set by getOrCreate
  • [SPARK-23966][SS] Refactoring all checkpoint file writing logic in a common CheckpointFileManager interface
  • [SPARK-21351][SQL] Update nullability based on children’s output
  • [SPARK-23847][PYTHON][SQL] Add asc_nulls_first, asc_nulls_last to PySpark
  • [SPARK-23822][SQL] Improve error message for Parquet schema mismatches
  • [SPARK-23823][SQL] Keep origin in transformExpression
  • [SPARK-23838][WEBUI] Running SQL query is displayed as “completed” in SQL tab
  • [SPARK-23802][SQL] PropagateEmptyRelation can leave query plan in unresolved state
  • [SPARK-23727][SQL] Support for pushing down filters for DateType in parquet
  • [SPARK-23574][SQL] Report SinglePartition in DataSourceV2ScanExec when there’s exactly 1 data reader factory.
  • [SPARK-23533][SS] Add support for changing ContinuousDataReader’s startOffset
  • [SPARK-23491][SS] Remove explicit job cancellation from ContinuousExecution reconfiguring
  • [SPARK-23040][CORE] Returns interruptible iterator for shuffle reader
  • [SPARK-23827][SS] StreamingJoinExec should ensure that input data is partitioned into specific number of partitions
  • [SPARK-23639][SQL] Obtain token before init metastore client in SparkSQL CLI
  • [SPARK-23806]Broadcast.unpersist can cause fatal exception when used…
  • [SPARK-23599][SQL] Use RandomUUIDGenerator in Uuid expression
  • [SPARK-23599][SQL] Add a UUID generator from Pseudo-Random Numbers
  • [SPARK-23759][UI] Unable to bind Spark UI to specific host name / IP
  • [SPARK-23769][CORE] Remove comments that unnecessarily disable Scalastyle check
  • [SPARK-23614][SQL] Fix incorrect reuse exchange when caching is used
  • [SPARK-23760][SQL] CodegenContext.withSubExprEliminationExprs should save/restore CSE state correctly
  • [SPARK-23729][CORE] Respect URI fragment when resolving globs
  • [SPARK-23550][CORE] Cleanup Utils
  • [SPARK-23288][SS] Fix output metrics with parquet sink
  • [SPARK-23264][SQL] Fix scala.MatchError in literals.sql.out
  • [SPARK-23649][SQL] Skipping chars disallowed in UTF-8
  • [SPARK-23691][PYTHON] Use sql_conf util in PySpark tests where possible
  • [SPARK-23644][CORE][UI] Use absolute path for REST call in SHS
  • [SPARK-23706][PYTHON] spark.conf.get(value, default=None) should produce None in PySpark
  • [SPARK-23623][SS] Avoid concurrent use of cached consumers in CachedKafkaConsumer
  • [SPARK-23670][SQL] Fix memory leak on SparkPlanGraphWrapper
  • [SPARK-23608][CORE][WEBUI] Add synchronization in SHS between attachSparkUI and detachSparkUI functions to avoid concurrent modification issue to Jetty Handlers
  • [SPARK-23671][CORE] Fix condition to enable the SHS thread pool.
  • [SPARK-23658][LAUNCHER] InProcessAppHandle uses the wrong class in getLogger
  • [SPARK-23642][DOCS] AccumulatorV2 subclass isZero scaladoc fix
  • [SPARK-22915][MLLIB] Streaming tests for, from N to Z
  • [SPARK-23598][SQL] Make methods in BufferedRowIterator public to avoid runtime error for a large query
  • [SPARK-23546][SQL] Refactor stateless methods/values in CodegenContext
  • [SPARK-23523][SQL] Fix the incorrect result caused by the rule OptimizeMetadataOnlyQuery
  • [SPARK-23462][SQL] improve missing field error message in StructType
  • [SPARK-23624][SQL] Revise doc of method pushFilters in Datasource V2
  • [SPARK-23173][SQL] Avoid creating corrupt parquet files when loading data from JSON
  • [SPARK-23436][SQL] Infer partition as Date only if it can be casted to Date
  • [SPARK-23406][SS] Enable stream-stream self-joins
  • [SPARK-23490][SQL] Check storage.locationUri with existing table in CreateTable
  • [SPARK-23524]Big local shuffle blocks should not be checked for corruption.
  • [SPARK-23525][SQL] Support ALTER TABLE CHANGE COLUMN COMMENT for external hive table
  • [SPARK-23434][SQL] Spark should not warn metadata directory for a HDFS file path
  • [SPARK-23457][SQL] Register task completion listeners first in ParquetFileFormat
  • [SPARK-23329][SQL] Fix documentation of trigonometric functions
  • [SPARK-23569][PYTHON] Allow pandas_udf to work with python3 style type-annotated functions
  • [SPARK-23570][SQL] Add Spark 2.3.0 in HiveExternalCatalogVersionsSuite
  • [SPARK-23517][PYTHON] Make pyspark.util._exception_message produce the trace from Java side by Py4JJavaError
  • [SPARK-23508][CORE] Fix BlockmanagerId in case blockManagerIdCache cause oom
  • [SPARK-23448][SQL] Clarify JSON and CSV parser behavior in document
  • [SPARK-23365][CORE] Do not adjust num executors when killing idle executors.
  • [SPARK-23438][DSTREAMS] Fix DStreams data loss with WAL when driver crashes
  • [SPARK-23475][UI] Show also skipped stages
  • [SPARK-23518][SQL] Avoid metastore access when the users only want to read and write data frames
  • [SPARK-23406][SS] Enable stream-stream self-joins
  • [SPARK-23541][SS] Allow Kafka source to read data with greater parallelism than the number of topic-partitions
  • [SPARK-23097][SQL][SS] Migrate text socket source to V2
  • [SPARK-23362][SS] Migrate Kafka Microbatch source to v2
  • [SPARK-23445]ColumnStat refactoring
  • [SPARK-23092][SQL] Migrate MemoryStream to DataSourceV2 APIs
  • [SPARK-23447][SQL] Cleanup codegen template for Literal
  • [SPARK-23366]Improve hot reading path in ReadAheadInputStream
  • [SPARK-22624][PYSPARK] Expose range partitioning shuffle

Maintenance Updates

Maintenance updates made to Databricks Runtime 4.1 since its initial release include:

  • Jan 8, 2019
    • [SPARK-26366]ReplaceExceptWithFilter should consider NULL as False.
    • Delta Lake is enabled.
  • Dec 18, 2018
    • [SPARK-25002]Avro: revise the output record namespace.
    • Fixed an issue affecting certain queries using Join and Limit.
    • [SPARK-26307]Fixed CTAS when INSERT a partitioned table using Hive SerDe.
    • Only ignore corrupt files after one or more retries when spark.sql.files.ignoreCorruptFiles or spark.sql.files.ignoreMissingFiles flag is enabled.
    • Fixed an issue affecting installing Python Wheels in environments without Internet access.
    • Fixed an issue in PySpark that caused DataFrame actions failed with “connection refused” error.
    • Fixed an issue affecting certain self union queries.
  • Nov 20, 2018
    • [SPARK-17916][SPARK-25241]Fix empty string being parsed as null when nullValue is set.
    • Fixed an issue affecting certain aggregation queries with Left Semi/Anti joins.
  • Nov 6, 2018
    • [SPARK-25741]Long URLs are not rendered properly in web UI.
    • [SPARK-25714]Fix Null Handling in the Optimizer rule BooleanSimplification.
  • Oct 9, 2018
    • Fixed a bug affecting the output of running SHOW CREATE TABLE on Delta Lake tables.
    • Fixed a bug affecting Union operation.
  • Sep 25, 2018
    • [SPARK-25368][SQL] Incorrect constraint inference returns wrong result.
    • [SPARK-25402][SQL] Null handling in BooleanSimplification.
    • Fixed NotSerializableException in Avro data source.
  • Sep 11, 2018
    • [SPARK-25214][SS] Fix the issue that Kafka v2 source may return duplicated records when failOnDataLoss=false.
    • [SPARK-24987][SS] Fix Kafka consumer leak when no new offsets for TopicPartition.
    • Filter reduction should handle null value correctly.
  • Aug 28, 2018
    • Fixed a bug in Delta Lake Delete command that would incorrectly delete the rows where the condition evaluates to null.
    • [SPARK-25084]“distribute by” on multiple columns (wrap in brackets) may lead to codegen issue.
    • [SPARK-25114]Fix RecordBinaryComparator when subtraction between two words is divisible by Integer.MAX_VALUE.
  • Aug 23, 2018
    • Fixed NoClassDefError for Delta Snapshot.
    • [SPARK-24957][SQL] Average with decimal followed by aggregation returns wrong result. The incorrect results of AVERAGE might be returned. The CAST added in the Average operator will be bypassed if the result of Divide is the same type which it is casted to.
    • Fixed nullable map issue in Parquet reader.
    • [SPARK-24934][SQL] Explicitly whitelist supported types in upper/lower bounds for in-memory partition pruning. When complex data types are used in query filters against cached data, Spark always returns an empty result set. The in-memory stats-based pruning generates incorrect results, because null is set for upper/lower bounds for complex types. The fix is to not use in-memory stats-based pruning for complex types.
    • [SPARK-25081]Fixed a bug where ShuffleExternalSorter may access a released memory page when spilling fails to allocate memory.
    • Fixed an interaction between Databricks Delta and Pyspark which could cause transient read failures.
    • Fixed secret manager redaction when command partially succeed
  • Aug 2, 2018
    • [SPARK-24613][SQL] Cache with UDF could not be matched with subsequent dependent caches. Wraps the logical plan with a AnalysisBarrier for execution plan compilation in CacheManager, in order to avoid the plan being analyzed again. This is also a regression of Spark 2.3.
    • Fixed a SQL Data Warehouse connector issue affecting timezone conversion for writing DateType data.
    • Fixed an issue affecting Delta checkpointing.
    • Fixed an issue that could cause mergeInto command to produce incorrect results.
    • [SPARK-24867][SQL] Add AnalysisBarrier to DataFrameWriter. SQL cache is not being used when using DataFrameWriter to write a DataFrame with UDF. This is a regression caused by the changes we made in AnalysisBarrier, since not all the Analyzer rules are idempotent.
    • [SPARK-24809]Serializing LongHashedRelation in executor may result in data error.
  • July 11, 2018
    • Fixed a bug in query execution that would cause aggregations on decimal columns with different precisions to return incorrect results in some cases.
    • Fixed a NullPointerException bug that was thrown during advanced aggregation operations like grouping sets.
  • June 28, 2018
    • Fixed a bug that could cause incorrect query results when the name of a partition column used in a predicate differs from the case of that column in the schema of the table.
  • May 29, 2018
    • Fixed a bug affecting Spark SQL execution engine.
    • Fixed a bug affecting code generation.
    • Fixed a bug (java.lang.NoClassDefFoundError) affecting Delta.
    • Improved error handling in Delta.
  • May 15, 2018
    • Fixed a bug that caused incorrect data skipping statistics to be collected for string columns 32 characters or greater.

System Environment

  • Operating System: Ubuntu 16.04.4 LTS
  • Java: 1.8.0_162
  • Scala: 2.11.8
  • Python: 2.7.12 for Python 2 clusters and 3.5.2 for Python 3 clusters. For details, see Python Clusters.
  • R: R version 3.4.4 (2018-03-15)
  • GPU clusters: The following NVIDIA GPU libraries are installed:
    • Tesla driver 375.66
    • CUDA 9.0
    • cuDNN 7.0

Installed Python Libraries

Library Version Library Version Library Version
ansi2html 1.1.1 argparse 1.2.1 backports-abc 0.5
boto 2.42.0 boto3 1.4.1 botocore 1.4.70
brewer2mpl 1.4.1 certifi 2016.2.28 cffi 1.7.0
chardet 2.3.0 colorama 0.3.7 configobj 5.0.6
cryptography 1.5 cycler 0.10.0 Cython 0.24.1
decorator 4.0.10 docutils 0.14 enum34 1.1.6
et-xmlfile 1.0.1 freetype-py 1.0.2 funcsigs 1.0.2
fusepy 2.0.4 futures 3.2.0 ggplot 0.6.8
html5lib 0.999 idna 2.1 ipaddress 1.0.16
ipython 2.2.0 ipython-genutils 0.1.0 jdcal 1.2
Jinja2 2.8 jmespath 0.9.0 llvmlite 0.13.0
lxml 3.6.4 MarkupSafe 0.23 matplotlib 1.5.3
mpld3 0.2 msgpack-python 0.4.7 ndg-httpsclient 0.3.3
numba 0.28.1 numpy 1.11.1 openpyxl 2.3.2
pandas 0.19.2 pathlib2 2.1.0 patsy 0.4.1
pexpect 4.0.1 pickleshare 0.7.4 Pillow 3.3.1
pip 10.0.0b2 ply 3.9 prompt-toolkit 1.0.7
psycopg2 2.6.2 ptyprocess 0.5.1 py4j 0.10.3
pyarrow 0.8.0 pyasn1 0.1.9 pycparser 2.14
Pygments 2.1.3 PyGObject 3.20.0 pyOpenSSL 16.0.0
pyparsing 2.2.0 pypng 0.0.18 Python 2.7.12
python-dateutil 2.5.3 python-geohash 0.8.5 pytz 2016.6.1
requests 2.11.1 s3transfer 0.1.9 scikit-learn 0.18.1
scipy 0.18.1 scour 0.32 seaborn 0.7.1
setuptools 39.0.1 simplejson 3.8.2 simples3 1.0
singledispatch six 1.10.0 statsmodels 0.6.1
tornado 5.0.1 traitlets 4.3.0 urllib3 1.19.1
virtualenv 15.0.1 wcwidth 0.1.7 wheel 0.31.0
wsgiref 0.1.2        

Installed R Libraries

Library Version Library Version Library Version
abind 1.4-5 assertthat 0.2.0 backports 1.1.2
base 3.4.4 BH 1.66.0-1 bindr 0.1.1
bindrcpp 0.2.2 bit 1.1-12 bit64 0.9-7
bitops 1.0-6 blob 1.1.1 boot 1.3-20
brew 1.0-6 broom 0.4.4 car 3.0-0
carData 3.0-1 caret 6.0-79 cellranger 1.1.0
chron 2.3-52 class 7.3-14 cli 1.0.0
cluster 2.0.7 codetools 0.2-15 colorspace 1.3-2
commonmark 1.4 compiler 3.4.4 crayon 1.3.4
curl 3.2 CVST 0.2-1 data.table 1.10.4-3
datasets 3.4.4 DBI 0.8 ddalpha
DEoptimR 1.0-8 desc 1.1.1 devtools 1.13.5
dichromat 2.0-0 digest 0.6.15 dimRed 0.1.0
doMC 1.3.5 dplyr 0.7.4 DRR 0.0.3
forcats 0.3.0 foreach 1.4.4 foreign 0.8-69
gbm 2.1.3 ggplot2 2.2.1 git2r 0.21.0
glmnet 2.0-16 glue 1.2.0 gower 0.1.2
graphics 3.4.4 grDevices 3.4.4 grid 3.4.4
gsubfn 0.7 gtable 0.2.0 h2o
haven 1.1.1 hms 0.4.2 httr 1.3.1
hwriter 1.3.2 hwriterPlus 1.0-3 ipred 0.9-6
iterators 1.0.9 jsonlite 1.5 kernlab 0.9-25
KernSmooth 2.23-15 labeling 0.3 lattice 0.20-35
lava 1.6.1 lazyeval 0.2.1 littler 0.3.3
lme4 1.1-17 lubridate 1.7.3 magrittr 1.5
mapproj 1.2.6 maps 3.3.0 maptools 0.9-2
MASS 7.3-49 Matrix 1.2-13 MatrixModels 0.4-1
memoise 1.1.0 methods 3.4.4 mgcv 1.8-23
mime 0.5 minqa 1.2.4 mnormt 1.5-5
ModelMetrics 1.1.0 munsell 0.4.3 mvtnorm 1.0-7
nlme 3.1-137 nloptr 1.0.4 nnet 7.3-12
numDeriv 2016.8-1 openssl 1.0.1 openxlsx 4.0.17
parallel 3.4.4 pbkrtest 0.4-7 pillar 1.2.1
pkgconfig 2.0.1 pkgKitten 0.1.4 plogr 0.2.0
plyr 1.8.4 praise 1.0.0 prettyunits 1.0.2
pROC 1.11.0 prodlim 1.6.1 proto 1.0.0
psych purrr 0.2.4 quantreg 5.35
R.methodsS3 1.7.1 R.oo 1.21.0 R.utils 2.6.0
R6 2.2.2 randomForest 4.6-14 RColorBrewer 1.1-2
Rcpp 0.12.16 RcppEigen RcppRoll 0.2.2
RCurl 1.95-4.10 readr 1.1.1 readxl 1.0.0
recipes 0.1.2 rematch 1.0.1 reshape2 1.4.3
rio 0.5.10 rlang 0.2.0 robustbase 0.92-8
RODBC 1.3-15 roxygen2 6.0.1 rpart 4.1-13
rprojroot 1.3-2 Rserve 1.7-3 RSQLite 2.1.0
rstudioapi 0.7 scales 0.5.0 sfsmisc 1.1-2
sp 1.2-7 SparkR 2.3.0 SparseM 1.77
spatial 7.3-11 splines 3.4.4 sqldf 0.4-11
SQUAREM 2017.10-1 statmod 1.4.30 stats 3.4.4
stats4 3.4.4 stringi 1.1.7 stringr 1.3.0
survival 2.41-3 tcltk 3.4.4 TeachingDemos 2.10
testthat 2.0.0 tibble 1.4.2 tidyr 0.8.0
tidyselect 0.2.4 timeDate 3043.102 tools 3.4.4
utf8 1.1.3 utils 3.4.4 viridisLite 0.3.0
whisker 0.3-2 withr 2.1.2 xml2 1.2.0

Installed Java and Scala libraries (Scala 2.11 cluster version)

Group ID Artifact ID Version
antlr antlr 2.7.7
com.amazonaws amazon-kinesis-client 1.7.3
com.amazonaws aws-java-sdk-autoscaling 1.11.313
com.amazonaws aws-java-sdk-cloudformation 1.11.313
com.amazonaws aws-java-sdk-cloudfront 1.11.313
com.amazonaws aws-java-sdk-cloudhsm 1.11.313
com.amazonaws aws-java-sdk-cloudsearch 1.11.313
com.amazonaws aws-java-sdk-cloudtrail 1.11.313
com.amazonaws aws-java-sdk-cloudwatch 1.11.313
com.amazonaws aws-java-sdk-cloudwatchmetrics 1.11.313
com.amazonaws aws-java-sdk-codedeploy 1.11.313
com.amazonaws aws-java-sdk-cognitoidentity 1.11.313
com.amazonaws aws-java-sdk-cognitosync 1.11.313
com.amazonaws aws-java-sdk-config 1.11.313
com.amazonaws aws-java-sdk-core 1.11.313
com.amazonaws aws-java-sdk-datapipeline 1.11.313
com.amazonaws aws-java-sdk-directconnect 1.11.313
com.amazonaws aws-java-sdk-directory 1.11.313
com.amazonaws aws-java-sdk-dynamodb 1.11.313
com.amazonaws aws-java-sdk-ec2 1.11.313
com.amazonaws aws-java-sdk-ecs 1.11.313
com.amazonaws aws-java-sdk-efs 1.11.313
com.amazonaws aws-java-sdk-elasticache 1.11.313
com.amazonaws aws-java-sdk-elasticbeanstalk 1.11.313
com.amazonaws aws-java-sdk-elasticloadbalancing 1.11.313
com.amazonaws aws-java-sdk-elastictranscoder 1.11.313
com.amazonaws aws-java-sdk-emr 1.11.313
com.amazonaws aws-java-sdk-glacier 1.11.313
com.amazonaws aws-java-sdk-iam 1.11.313
com.amazonaws aws-java-sdk-importexport 1.11.313
com.amazonaws aws-java-sdk-kinesis 1.11.313
com.amazonaws aws-java-sdk-kms 1.11.313
com.amazonaws aws-java-sdk-lambda 1.11.313
com.amazonaws aws-java-sdk-logs 1.11.313
com.amazonaws aws-java-sdk-machinelearning 1.11.313
com.amazonaws aws-java-sdk-opsworks 1.11.313
com.amazonaws aws-java-sdk-rds 1.11.313
com.amazonaws aws-java-sdk-redshift 1.11.313
com.amazonaws aws-java-sdk-route53 1.11.313
com.amazonaws aws-java-sdk-s3 1.11.313
com.amazonaws aws-java-sdk-ses 1.11.313
com.amazonaws aws-java-sdk-simpledb 1.11.313
com.amazonaws aws-java-sdk-simpleworkflow 1.11.313
com.amazonaws aws-java-sdk-sns 1.11.313
com.amazonaws aws-java-sdk-sqs 1.11.313
com.amazonaws aws-java-sdk-ssm 1.11.313
com.amazonaws aws-java-sdk-storagegateway 1.11.313
com.amazonaws aws-java-sdk-sts 1.11.313
com.amazonaws aws-java-sdk-support 1.11.313
com.amazonaws aws-java-sdk-swf-libraries 1.11.22
com.amazonaws aws-java-sdk-workspaces 1.11.313
com.amazonaws jmespath-java 1.11.313
com.carrotsearch hppc 0.7.2
com.chuusai shapeless_2.11 2.3.2 stream 2.7.0
com.databricks Rserve 1.8-3
com.databricks dbml-local_2.11 0.4.1-db1-spark2.3
com.databricks dbml-local_2.11-tests 0.4.1-db1-spark2.3
com.databricks jets3t 0.7.1-0
com.databricks.scalapb compilerplugin_2.11 0.4.15-9
com.databricks.scalapb scalapb-runtime_2.11 0.4.15-9
com.esotericsoftware kryo-shaded 3.0.3
com.esotericsoftware minlog 1.3.0
com.fasterxml classmate 1.0.0
com.fasterxml.jackson.core jackson-annotations 2.6.7
com.fasterxml.jackson.core jackson-core 2.6.7
com.fasterxml.jackson.core jackson-databind
com.fasterxml.jackson.dataformat jackson-dataformat-cbor 2.6.7
com.fasterxml.jackson.datatype jackson-datatype-joda 2.6.7
com.fasterxml.jackson.module jackson-module-paranamer 2.6.7
com.fasterxml.jackson.module jackson-module-scala_2.11
com.github.fommil jniloader 1.1
com.github.fommil.netlib core 1.1.2
com.github.fommil.netlib native_ref-java 1.1
com.github.fommil.netlib native_ref-java-natives 1.1
com.github.fommil.netlib native_system-java 1.1
com.github.fommil.netlib native_system-java-natives 1.1
com.github.fommil.netlib netlib-native_ref-linux-x86_64-natives 1.1
com.github.fommil.netlib netlib-native_system-linux-x86_64-natives 1.1
com.github.luben zstd-jni 1.3.2-2
com.github.rwl jtransforms 2.4.0 jsr305 2.0.1 gson 2.2.4 guava 15.0 protobuf-java 2.6.1
com.googlecode.javaewah JavaEWAH 0.3.2
com.h2database h2 1.3.174
com.jamesmurty.utils java-xmlbuilder 1.1
com.jcraft jsch 0.1.50
com.jolbox bonecp 0.8.0.RELEASE
com.mchange c3p0
com.mchange mchange-commons-java 0.2.10 azure-data-lake-store-sdk 2.2.8 mssql-jdbc 6.2.2.jre8
com.ning compress-lzf 1.0.3
com.sun.mail javax.mail 1.5.2
com.thoughtworks.paranamer paranamer 2.8
com.trueaccord.lenses lenses_2.11 0.3
com.twitter chill-java 0.8.4
com.twitter chill_2.11 0.8.4
com.twitter parquet-hadoop-bundle 1.6.0
com.twitter util-app_2.11 6.23.0
com.twitter util-core_2.11 6.23.0
com.twitter util-jvm_2.11 6.23.0
com.typesafe config 1.2.1
com.typesafe.scala-logging scala-logging-api_2.11 2.1.2
com.typesafe.scala-logging scala-logging-slf4j_2.11 2.1.2
com.univocity univocity-parsers 2.5.9
com.vlkan flatbuffers 1.2.0-3f79e055
com.zaxxer HikariCP 2.4.1
commons-beanutils commons-beanutils 1.7.0
commons-beanutils commons-beanutils-core 1.8.0
commons-cli commons-cli 1.2
commons-codec commons-codec 1.10
commons-collections commons-collections 3.2.2
commons-configuration commons-configuration 1.6
commons-dbcp commons-dbcp 1.4
commons-digester commons-digester 1.8
commons-httpclient commons-httpclient 3.1
commons-io commons-io 2.4
commons-lang commons-lang 2.6
commons-logging commons-logging 1.1.3
commons-net commons-net 2.2
commons-pool commons-pool 1.5.4
info.ganglia.gmetric4j gmetric4j 1.0.7
io.airlift aircompressor 0.8
io.dropwizard.metrics metrics-core 3.1.5
io.dropwizard.metrics metrics-ganglia 3.1.5
io.dropwizard.metrics metrics-graphite 3.1.5
io.dropwizard.metrics metrics-healthchecks 3.1.5
io.dropwizard.metrics metrics-jetty9 3.1.5
io.dropwizard.metrics metrics-json 3.1.5
io.dropwizard.metrics metrics-jvm 3.1.5
io.dropwizard.metrics metrics-log4j 3.1.5
io.dropwizard.metrics metrics-servlets 3.1.5
io.netty netty 3.9.9.Final
io.netty netty-all 4.1.17.Final
io.prometheus simpleclient 0.0.16
io.prometheus simpleclient_common 0.0.16
io.prometheus simpleclient_dropwizard 0.0.16
io.prometheus simpleclient_servlet 0.0.16
io.prometheus.jmx collector 0.7
javax.activation activation 1.1.1
javax.annotation javax.annotation-api 1.2
javax.el javax.el-api 2.2.4
javax.jdo jdo-api 3.0.1
javax.servlet javax.servlet-api 3.1.0
javax.servlet.jsp jsp-api 2.1
javax.transaction jta 1.1
javax.validation validation-api 1.1.0.Final 2.0.1
javax.xml.bind jaxb-api 2.2.2 stax-api 1.0-2
javolution javolution 5.5.1
jline jline 2.11
joda-time joda-time 2.9.3
log4j apache-log4j-extras 1.2.17
log4j log4j 1.2.17
net.hydromatic eigenbase-properties 1.1.5
net.iharder base64 2.3.8 jets3t 0.9.4
net.razorvine pyrolite 4.13
net.sf.jpam jpam 1.1
net.sf.opencsv opencsv 2.3
net.sf.supercsv super-csv 2.2.0
net.sourceforge.f2j arpack_combined_all 0.1
org.acplt oncrpc 1.0.7
org.antlr ST4 4.0.4
org.antlr antlr-runtime 3.4
org.antlr antlr4-runtime 4.7
org.antlr stringtemplate 3.2.1
org.apache.ant ant 1.9.2
org.apache.ant ant-jsch 1.9.2
org.apache.ant ant-launcher 1.9.2
org.apache.arrow arrow-format 0.8.0
org.apache.arrow arrow-memory 0.8.0
org.apache.arrow arrow-vector 0.8.0
org.apache.avro avro 1.7.7
org.apache.avro avro-ipc 1.7.7
org.apache.avro avro-ipc-tests 1.7.7
org.apache.avro avro-mapred-hadoop2 1.7.7
org.apache.calcite calcite-avatica 1.2.0-incubating
org.apache.calcite calcite-core 1.2.0-incubating
org.apache.calcite calcite-linq4j 1.2.0-incubating
org.apache.commons commons-compress 1.4.1
org.apache.commons commons-crypto 1.0.0
org.apache.commons commons-lang3 3.5
org.apache.commons commons-math3 3.4.1
org.apache.curator curator-client 2.7.1
org.apache.curator curator-framework 2.7.1
org.apache.curator curator-recipes 2.7.1
org.apache.derby derby api-asn1-api 1.0.0-M20 api-util 1.0.0-M20 apacheds-i18n 2.0.0-M15 apacheds-kerberos-codec 2.0.0-M15
org.apache.hadoop hadoop-annotations 2.7.3
org.apache.hadoop hadoop-auth 2.7.3
org.apache.hadoop hadoop-client 2.7.3
org.apache.hadoop hadoop-common 2.7.3
org.apache.hadoop hadoop-hdfs 2.7.3
org.apache.hadoop hadoop-mapreduce-client-app 2.7.3
org.apache.hadoop hadoop-mapreduce-client-common 2.7.3
org.apache.hadoop hadoop-mapreduce-client-core 2.7.3
org.apache.hadoop hadoop-mapreduce-client-jobclient 2.7.3
org.apache.hadoop hadoop-mapreduce-client-shuffle 2.7.3
org.apache.hadoop hadoop-yarn-api 2.7.3
org.apache.hadoop hadoop-yarn-client 2.7.3
org.apache.hadoop hadoop-yarn-common 2.7.3
org.apache.hadoop hadoop-yarn-server-common 2.7.3
org.apache.htrace htrace-core 3.1.0-incubating
org.apache.httpcomponents httpclient 4.5.4
org.apache.httpcomponents httpcore 4.4.8
org.apache.ivy ivy 2.4.0
org.apache.orc orc-core-nohive 1.4.1
org.apache.orc orc-mapreduce-nohive 1.4.1
org.apache.parquet parquet-column 1.8.2-databricks1
org.apache.parquet parquet-common 1.8.2-databricks1
org.apache.parquet parquet-encoding 1.8.2-databricks1
org.apache.parquet parquet-format 2.3.1
org.apache.parquet parquet-hadoop 1.8.2-databricks1
org.apache.parquet parquet-jackson 1.8.2-databricks1
org.apache.thrift libfb303 0.9.3
org.apache.thrift libthrift 0.9.3
org.apache.xbean xbean-asm5-shaded 4.4
org.apache.zookeeper zookeeper 3.4.6
org.bouncycastle bcprov-jdk15on 1.58
org.codehaus.jackson jackson-core-asl 1.9.13
org.codehaus.jackson jackson-jaxrs 1.9.13
org.codehaus.jackson jackson-mapper-asl 1.9.13
org.codehaus.jackson jackson-xc 1.9.13
org.codehaus.janino commons-compiler 3.0.8
org.codehaus.janino janino 3.0.8
org.datanucleus datanucleus-api-jdo 3.2.6
org.datanucleus datanucleus-core 3.2.10
org.datanucleus datanucleus-rdbms 3.2.9
org.eclipse.jetty jetty-client 9.3.20.v20170531
org.eclipse.jetty jetty-continuation 9.3.20.v20170531
org.eclipse.jetty jetty-http 9.3.20.v20170531
org.eclipse.jetty jetty-io 9.3.20.v20170531
org.eclipse.jetty jetty-jndi 9.3.20.v20170531
org.eclipse.jetty jetty-plus 9.3.20.v20170531
org.eclipse.jetty jetty-proxy 9.3.20.v20170531
org.eclipse.jetty jetty-security 9.3.20.v20170531
org.eclipse.jetty jetty-server 9.3.20.v20170531
org.eclipse.jetty jetty-servlet 9.3.20.v20170531
org.eclipse.jetty jetty-servlets 9.3.20.v20170531
org.eclipse.jetty jetty-util 9.3.20.v20170531
org.eclipse.jetty jetty-webapp 9.3.20.v20170531
org.eclipse.jetty jetty-xml 9.3.20.v20170531
org.fusesource.leveldbjni leveldbjni-all 1.8
org.glassfish.hk2 hk2-api 2.4.0-b34
org.glassfish.hk2 hk2-locator 2.4.0-b34
org.glassfish.hk2 hk2-utils 2.4.0-b34
org.glassfish.hk2 osgi-resource-locator 1.0.1
org.glassfish.hk2.external aopalliance-repackaged 2.4.0-b34
org.glassfish.hk2.external javax.inject 2.4.0-b34
org.glassfish.jersey.bundles.repackaged jersey-guava 2.22.2
org.glassfish.jersey.containers jersey-container-servlet 2.22.2
org.glassfish.jersey.containers jersey-container-servlet-core 2.22.2
org.glassfish.jersey.core jersey-client 2.22.2
org.glassfish.jersey.core jersey-common 2.22.2
org.glassfish.jersey.core jersey-server 2.22.2 jersey-media-jaxb 2.22.2
org.hibernate hibernate-validator 5.1.1.Final
org.iq80.snappy snappy 0.2
org.javassist javassist 3.18.1-GA
org.jboss.logging jboss-logging 3.1.3.GA
org.jdbi jdbi 2.63.1
org.joda joda-convert 1.7
org.jodd jodd-core 3.5.2
org.json4s json4s-ast_2.11 3.2.11
org.json4s json4s-core_2.11 3.2.11
org.json4s json4s-jackson_2.11 3.2.11
org.lz4 lz4-java 1.4.0
org.mariadb.jdbc mariadb-java-client 2.1.2
org.mockito mockito-all 1.9.5
org.objenesis objenesis 2.1
org.postgresql postgresql 42.1.4
org.roaringbitmap RoaringBitmap 0.5.11
org.rocksdb rocksdbjni 5.2.1
org.rosuda.REngine REngine 2.1.0
org.scala-lang scala-compiler_2.11 2.11.8
org.scala-lang scala-library_2.11 2.11.8
org.scala-lang scala-reflect_2.11 2.11.8
org.scala-lang scalap_2.11 2.11.8
org.scala-lang.modules scala-parser-combinators_2.11 1.0.2
org.scala-lang.modules scala-xml_2.11 1.0.5
org.scala-sbt test-interface 1.0
org.scalacheck scalacheck_2.11 1.12.5
org.scalanlp breeze-macros_2.11 0.13.2
org.scalanlp breeze_2.11 0.13.2
org.scalatest scalatest_2.11 2.2.6
org.slf4j jcl-over-slf4j 1.7.16
org.slf4j jul-to-slf4j 1.7.16
org.slf4j slf4j-api 1.7.16
org.slf4j slf4j-log4j12 1.7.16
org.spark-project.hive hive-beeline 1.2.1.spark2
org.spark-project.hive hive-cli 1.2.1.spark2
org.spark-project.hive hive-exec 1.2.1.spark2
org.spark-project.hive hive-jdbc 1.2.1.spark2
org.spark-project.hive hive-metastore 1.2.1.spark2
org.spark-project.spark unused 1.0.0
org.spire-math spire-macros_2.11 0.13.0
org.spire-math spire_2.11 0.13.0
org.springframework spring-core 4.1.4.RELEASE
org.springframework spring-test 4.1.4.RELEASE
org.tukaani xz 1.0
org.typelevel machinist_2.11 0.6.1
org.typelevel macro-compat_2.11 1.1.1
org.xerial sqlite-jdbc
org.xerial.snappy snappy-java
org.yaml snakeyaml 1.16
oro oro 2.0.8 ion-java 1.0.2
stax stax-api 1.0.1
xmlenc xmlenc 0.52