Databricks Runtime 5.0 (不支援的) Databricks Runtime 5.0 (Unsupported)
Databricks 在2018年11月發行此映射。Databricks released this image in November 2018.
下列版本資訊提供 Apache Spark 所支援之 Databricks Runtime 5.0 的相關資訊。The following release notes provide information about Databricks Runtime 5.0, powered by Apache Spark.
新功能New Features
Delta LakeDelta Lake
- 子句現在支援和命令的子查詢
WHERE
DELETE
UPDATE
。Subqueries are now supported in theWHERE
clause for the support forDELETE
andUPDATE
commands. 請參閱 Azure Databricks) 上 (Delta Lake 刪除 ,並 在 Azure Databricks) 上更新 (Delta lake 。See Delete From (Delta Lake on Azure Databricks) and Update (Delta Lake on Azure Databricks). - 適用于命令的新可調整執行
MERGE
。New scalable implementation forMERGE
commands. 請參閱 Azure Databricks) 上的 Merge Into (Delta Lake 。See Merge Into (Delta Lake on Azure Databricks).- 插入和更新的數量沒有限制。No limit on the number of inserts and updates.
- 可以用於 SCD 類型1和類型2查詢。Can be used for SCD Type 1 and Type 2 queries. 請參閱 使用合併筆記本的範例 SCD 類型 2 。See example SCD Type 2 using MERGE notebook.
- 可以是從「更新」模式中的串流查詢執行 upsert (例如,將串流匯總輸出寫入至差異資料表) 。Can be to perform upserts from streaming queries in “update” mode (for example, write streaming aggregation output to a Delta table). 請參閱 使用 MERGE And foreachBatch 筆記本將串流匯總寫入 Databricks Delta 的範例。See example Writing streaming aggregates into Databricks Delta Using MERGE and foreachBatch notebook.
- 子句現在支援和命令的子查詢
結構化串流Structured Streaming
- 以 Azure Blob 儲存體檔案通知為基礎的串流來源。Azure Blob storage file notification based streaming source. 在 Azure Blob 儲存體中的檔案上執行結構化串流查詢時,這可能會大幅降低清單成本。This can significantly reduce listing costs when running a Structured Streaming query on files in Azure Blob storage. 此串流來源可以直接讀取檔案事件通知以尋找新檔案,而不是使用清單來尋找要處理的新檔案。Instead of using listing to find new files for processing, this streaming source can directly read file event notifications to find new files. 請參閱 使用 Azure 佇列儲存體的優化 Azure Blob 儲存體檔案來源。See Optimized Azure Blob storage file source with Azure Queue Storage.
新增對 TensorBoard 的支援,以監視深度學習工作。Added support for TensorBoard for monitoring deep learning jobs. 請參閱 TensorBoard。See TensorBoard.
改善Improvements
- Delta LakeDelta Lake
OPTIMIZE
效能和穩定性。OPTIMIZE
performance and stability.- 此
OPTIMIZE
命令會儘快認可批次,而不是在結尾。TheOPTIMIZE
command commits batches as soon as possible, instead of at the end. - 減少平行執行的預設執行緒數目
OPTIMIZE
。Reduced the default number of threadsOPTIMIZE
runs in parallel. 針對大型資料表,這是嚴格的效能提升。This is a strict performance increase for large tables. - 藉
OPTIMIZE
由在寫入資料分割資料表時避免不必要的排序資料,來加速寫入。Sped upOPTIMIZE
writes by avoiding an unnecessarily sorting data when writing to a partitioned table. - 藉
OPTIMIZE ZORDER BY
由使其遞增,來加速。Sped upOPTIMIZE ZORDER BY
by making it incremental. 這表示命令現在可避免重寫已經由相同資料行 (s) 排序的資料檔案。This means the command now avoids rewriting data files that were already Z-ordered by the same column(s). 請參閱 Z 順序 (多維度群集) 。See Z-Ordering (multi-dimensional clustering).
- 此
- 查詢 Delta 資料表時,快照集隔離。Snapshot isolation when querying Delta tables. 如果查詢具有差異資料表的多個參考 (例如,自我聯結) 會從相同的資料表快照集進行讀取,即使資料表有並行的更新也一樣。Any query with multiple references to a Delta table (for example, self-join) reads from the same table snapshot even if there are concurrent updates to the table.
- 藉由在驅動程式上快取中繼資料,來改善從小型 ( # A0 2000 檔案讀取) Delta 資料表的查詢延遲。Improved query latency when reading from small (< 2000 files) Delta tables by caching metadata on the driver.
- 改善 MLlib 羅吉斯回歸效能。Improved MLlib logistic regression performance.
- 改善的 MLlib 樹狀結構效能。Improved MLlib tree algorithm performance.
- 已升級數個 JAVA 和 Scala 程式庫。Upgraded several Java and Scala libraries. 請參閱 已安裝的 JAVA 和 Scala 程式庫 (Scala 2.11 叢集版本) 。See Installed Java and Scala libraries (Scala 2.11 cluster version).
- 已升級部分安裝的 Python 程式庫:Upgraded some installed Python libraries:
- pip:10.0.1 至18。0pip: 10.0.1 to 18.0
- setuptools:39.2.0 至40.4。1setuptools: 39.2.0 to 40.4.1
- 龍捲風:5.0.2 版至5.1。1tornado: 5.0.2 to 5.1.1
- 已升級數個已安裝的 R 程式庫。Upgraded several installed R libraries. 請參閱 已安裝的 R 程式庫。See Installed R Libraries.
Bug 修正Bug Fixes
- Delta LakeDelta Lake
- 在 SQL 會議中設定的設定現在會正確地套用到第一次載入不同筆記本的 Delta Lake 作業。Configurations set in SQL conf now correctly apply to Delta Lake operations that were first loaded in a different notebook.
- 修正了命令中的錯誤,此錯誤
DELETE
會不正確地刪除條件評估為 null 的資料列。Fixed a bug inDELETE
command that would incorrectly delete the rows where the condition evaluates to null. - 需要超過兩天來處理初始批次的資料流程 (也就是,當資料流程啟動時,資料表中的資料) 在
FileNotFoundException
嘗試從檢查點復原時不再失敗。Streams that take more than two days to process the initial batch (that is, data that was in the table when the stream started) no longer fail withFileNotFoundException
when attempting to recover from a checkpoint. - 避免在
NoClassDefError
載入新的資料表時造成的競爭情形。Avoids a race condition that lead toNoClassDefError
when loading a new table. - 修正作業
VACUUM
失敗的位置,並顯示 AssertionError,說明:「此處不應有任何絕對路徑可供刪除。」Fix forVACUUM
where the operation may fail with an AssertionError stating: “Shouldn’t have any absolute paths for deletion here.” - 固定
SHOW CREATE TABLE
的命令,不包含 Hive 產生的儲存體屬性。FixedSHOW CREATE TABLE
command to not include Hive-generated storage properties.
NoClassDefFoundError
針對內部 Spark 類別擲回許多錯誤的執行程式,現在會自動重新開機以修正問題。Executors that throw manyNoClassDefFoundError
errors for internal Spark classes are now automatically restarted to fix the issue.
已知問題Known Issues
replaceWhere
overwrite
即使已啟用不區分大小寫 ((預設) ),Delta Lake 中模式的選項所指定的資料行名稱仍會區分大小寫。Column names specified in thereplaceWhere
option foroverwrite
mode in Delta Lake are case sensitive even if case insensitivity is enabled (which is the default).- 適用于 Databricks Runtime 5.0 的 雪花連接器 目前為預覽狀態。The Snowflake connector for Databricks Runtime 5.0 is in Preview.
- 如果您在連接到 Databricks Runtime 5.0 叢集的筆記本中取消正在執行的串流資料格,除非您清除筆記本狀態或重新開機叢集,否則無法在筆記本中執行任何後續的命令。If you cancel a running streaming cell in a notebook attached to a Databricks Runtime 5.0 cluster, you cannot run any subsequent commands in the notebook unless you clear notebook state or restart the cluster. 如需解決方法,請參閱 知識庫。For a workaround, see the Knowledge Base.
Apache SparkApache Spark
Databricks Runtime 5.0 包括 Apache Spark 2.4.0。Databricks Runtime 5.0 includes Apache Spark 2.4.0.
Core 和 Spark SQLCore and Spark SQL
注意
本文包含詞彙 從屬 的參考,這是 Azure Databricks 不再使用的詞彙。This article contains references to the term slave, a term that Azure Databricks no longer uses. 從軟體中移除該字詞時,我們也會將其從本文中移除。When the term is removed from the software, we’ll remove it from this article.
主要功能Major features
- 屏障執行模式: [SPARK-24374] 支援排程器中的關卡執行模式,以更妥善地與深度學習架構整合。Barrier Execution Mode: [SPARK-24374] Support Barrier Execution Mode in the scheduler, to better integrate with deep learning frameworks.
- Scala 2.12 支援: [SPARK-14220] 新增實驗性 Scala 2.12 支援。Scala 2.12 Support: [SPARK-14220] Add experimental Scala 2.12 support. 現在您可以使用 Scala 2.12 建立 Spark,並在 Scala 2.12 中撰寫 Spark 應用程式。Now you can build Spark with Scala 2.12 and write Spark applications in Scala 2.12.
- 較高順序的函 式: [SPARK-23899] 新增許多新的內建函數,包括高序位函數,以便更輕鬆地使用複雜的資料類型。Higher-order functions: [SPARK-23899] Add many new built-in functions, including high-order functions, to make working with complex data types easier. 請參閱 Apache Spark 內建函數。See Apache Spark built-in functions.
- 內建 Avro 資料來源: [SPARK-24768] 具有邏輯類型支援的內嵌 Spark-Avro 套件、更佳的效能和可用性。Built-in Avro data source: [SPARK-24768] Inline Spark-Avro package with logical type support, better performance and usability.
APIAPI
- [SPARK-24035] Pivot 的 SQL 語法[SPARK-24035] SQL syntax for Pivot
- [SPARK-24940] SQL 查詢的聯合和重新分割提示[SPARK-24940] Coalesce and Repartition Hint for SQL Queries
- [SPARK-19602] 支援完整資料行名稱的資料行解析[SPARK-19602] Support column resolution of fully qualified column name
- [SPARK-21274] 除了 ALL 和 INTERSECT 之外,全部執行[SPARK-21274] Implement EXCEPT ALL and INTERSECT ALL
效能和穩定性Performance and stability
- [SPARK-16406] 大量資料行的參考解析應更快[SPARK-16406] Reference resolution for large number of columns should be faster
- [SPARK-23486] 快取 lookupFunctions 外部目錄中的函式名稱[SPARK-23486] Cache the function name from the external catalog for lookupFunctions
- [SPARK-23803] 支援 Bucket 剪除[SPARK-23803] Support Bucket Pruning
- [SPARK-24802] 優化規則排除[SPARK-24802] Optimization Rule Exclusion
- [SPARK-4502] Parquet 資料表的嵌套架構剪除[SPARK-4502] Nested schema pruning for Parquet tables
- [SPARK-24296] 支援大於 2 GB 的複寫區塊[SPARK-24296] Support replicating blocks larger than 2 GB
- [SPARK-24307] 支援從記憶體傳送超過2GB 的訊息[SPARK-24307] Support sending messages over 2GB from memory
- [SPARK-23243] RDD 上的隨機 + 重新分割可能會導致不正確的答案[SPARK-23243] Shuffle+Repartition on an RDD could lead to incorrect answers
- [SPARK-25181] 限制 BlockManager 主機和從屬執行緒集區的大小,降低網路速度緩慢時的記憶體負擔[SPARK-25181] Limited the size of BlockManager master and slave thread pools, lowering memory overhead when networking is slow
連接器Connectors
- [SPARK-23972] 將 Parquet 從1.8.2 更新為1.10。0[SPARK-23972] Update Parquet from 1.8.2 to 1.10.0
- [SPARK-25419] Parquet 述詞下推改進[SPARK-25419] Parquet predicate pushdown improvement
- [SPARK-23456] 原生 ORC 讀取器預設為開啟[SPARK-23456] Native ORC reader is on by default
- [SPARK-22279] 依預設,使用原生 ORC 讀取器來讀取 Hive serde 資料表[SPARK-22279] Use native ORC reader to read Hive serde tables by default
- [SPARK-21783] 依預設開啟 ORC 篩選準則下推[SPARK-21783] Turn on ORC filter push-down by default
- [SPARK-24959] 加速 JSON 和 CSV 的計數 ( # A1[SPARK-24959] Speed up count() for JSON and CSV
- [SPARK-24244] 僅剖析必要的資料行至 CSV 剖析器[SPARK-24244] Parsing only required columns to the CSV parser
- [SPARK-23786] CSV 架構驗證-不檢查資料行名稱[SPARK-23786] CSV schema validation - column names are not checked
- [SPARK-24423] 指定要從 JDBC 讀取之查詢的選項查詢[SPARK-24423] Option query for specifying the query to read from JDBC
- [SPARK-22814] JDBC 分割區資料行中的支援日期/時間戳記[SPARK-22814] Support Date/Timestamp in JDBC partition column
- [SPARK-24771] 將 Avro 從1.7.7 更新為1。8[SPARK-24771] Update Avro from 1.7.7 to 1.8
PySparkPySpark
- [SPARK-24215] 針對資料框架 Api 實行積極評估[SPARK-24215] Implement eager evaluation for DataFrame APIs
- [SPARK-22274] - [SPARK-22239]具有 pandas udf 的使用者定義彙總函式[SPARK-22274] - [SPARK-22239] User-defined aggregation functions with pandas udf
- [SPARK-24396] 新增適用于 Python 的結構化串流 ForeachWriter[SPARK-24396] Add Structured Streaming ForeachWriter for Python
- [SPARK-23874] 將 Apache 箭號升級至0.10。0[SPARK-23874] Upgrade Apache Arrow to 0.10.0
- [SPARK-25004] 新增 spark.executor pyspark。記憶體限制[SPARK-25004] Add spark.executor.pyspark.memory limit
- [SPARK-23030] 使用箭號串流格式來建立和收集 pandas 資料框架[SPARK-23030] Use Arrow stream format for creating from and collecting pandas DataFrames
- [SPARK-24624] 支援混合的 Python UDF 和純量 pandas UDF[SPARK-24624] Support mixture of Python UDF and Scalar pandas UDF
其他值得注意的變更Other notable changes
- [SPARK-24596] 非級聯快取失效[SPARK-24596] Non-cascading Cache Invalidation
- [SPARK-23880] 不要觸發任何用來快取資料的作業[SPARK-23880] Do not trigger any job for caching data
- [Spark-23510][spark-24312] 支援 hive 2.2 和 hive 2.3 中繼存放區[SPARK-23510][SPARK-24312] Support Hive 2.2 and Hive 2.3 metastore
- [SPARK-23711] 新增 UnsafeProjection 的 fallback 產生器[SPARK-23711] Add fallback generator for UnsafeProjection
- [SPARK-24626] 分析資料表命令中的平行處理位置大小計算[SPARK-24626] Parallelize location size calculation in Analyze Table command
程式設計指南: SPARK RDD 程式設計指南 和 spark SQL 資料框架和資料集指南。Programming guides: Spark RDD Programming Guide and Spark SQL DataFrames and Datasets Guide.
結構化串流Structured Streaming
主要功能Major features
- [SPARK-24565] 使用 foreachBatch (Python、Scala 和 JAVA) ,將每個 microbatch 的輸出資料列公開為數據框架[SPARK-24565] Exposed the output rows of each microbatch as a DataFrame using foreachBatch (Python, Scala, and Java)
- [SPARK-24396] 已新增適用于 foreach 和 ForeachWriter 的 Python API[SPARK-24396] Added Python API for foreach and ForeachWriter
- [SPARK-25005] 支援 "kafka",以從使用交易式生產者撰寫的 Kafka 主題讀取認可的記錄。[SPARK-25005] Support “kafka.isolation.level” to read only committed records from Kafka topics that are written using a transactional producer.
其他值得注意的變更Other notable changes
- [SPARK-24662] 支援在附加或完成模式中進行資料流程的限制運算子[SPARK-24662] Support the LIMIT operator for streams in Append or Complete mode
- [SPARK-24763] 從串流匯總中的值移除重複的索引鍵資料[SPARK-24763] Remove redundant key data from value in streaming aggregation
- [SPARK-24156] 在輸入資料流程中沒有任何資料時,使用可設定狀態的作業加快產生輸出結果及/或狀態清除 (mapGroupsWithState、串流串流聯結、串流匯總、串流 dropDuplicates) 。[SPARK-24156] Faster generation of output results and/or state cleanup with stateful operations (mapGroupsWithState, stream-stream join, streaming aggregation, streaming dropDuplicates) when there is no data in the input stream.
- [SPARK-24730] 支援在查詢中有多個輸入資料流程時,選擇最小或最大水位線[SPARK-24730] Support for choosing either the min or max watermark when there are multiple input streams in a query
- [SPARK-25399] 修正了針對 microbatch 串流重複使用執行執行緒來自連續處理的錯誤,可能會導致正確性問題[SPARK-25399] Fixed a bug where reusing execution threads from continuous processing for microbatch streaming can result in a correctness issue
- [SPARK-18057] 從0.10.0.1 升級至2.0.0 的 Kafka 用戶端版本[SPARK-18057] Upgraded Kafka client version from 0.10.0.1 to 2.0.0
程式設計指南: 結構化串流程式設計指南。Programming guide: Structured Streaming Programming Guide.
MLlibMLlib
主要功能Major features
- [SPARK-22666] 適用于影像格式的 Spark 資料來源[SPARK-22666] Spark datasource for image format
其他值得注意的變更Other notable changes
- [Spark-22119][spark-23412][spark-23217] 將余弦距離量值新增至 KMeans/BisectingKMeans/叢集評估工具[SPARK-22119][SPARK-23412][SPARK-23217] Add cosine distance measure to KMeans/BisectingKMeans/Clustering evaluator
- [SPARK-10697] 關聯規則挖掘中的增益計算[SPARK-10697] Lift Calculation in Association Rule mining
- [Spark-14682][spark-24231] 提供 spark.ml gbt 的 evaluateEachIteration 方法或對等專案[SPARK-14682][SPARK-24231] Provide evaluateEachIteration method or equivalent for spark.ml GBTs
- [Spark-7132][SPARK-24333] 新增適用于驗證設定為 spark.ml GBT 的大小[SPARK-7132][SPARK-24333] Add fit with validation set to spark.ml GBT
- [Spark-15784][spark-19826] 將 Power 反覆運算叢集新增至 spark.ml[SPARK-15784][SPARK-19826] Add Power Iteration Clustering to spark.ml
- [SPARK-15064] StopWordsRemover 中的地區設定支援[SPARK-15064] Locale support in StopWordsRemover
- [SPARK-21741] 以資料框架為基礎的多變數摘要器的 Python API[SPARK-21741] Python API for DataFrame-based multivariate summarizer
- [Spark-21898][spark-23751] MLlib 中 KolmogorovSmirnovTest 的功能同位[SPARK-21898][SPARK-23751] Feature parity for KolmogorovSmirnovTest in MLlib
- [SPARK-10884] 支援針對回歸和分類相關模型的單一實例進行預測[SPARK-10884] Support prediction on single instance for regression and classification related models
- [SPARK-23783] 為 ML 管線新增一般匯出特性[SPARK-23783] Add new generic export trait for ML pipelines
- [SPARK-11239] ML 線性回歸的 PMML 匯出[SPARK-11239] PMML export for ML linear regression
程式設計指南: Machine Learning 程式庫 (MLlib) 指南。Programming guide: Machine Learning Library (MLlib) Guide.
SparkRSparkR
- [SPARK-25393] 新增函式 from_csv ( # A1[SPARK-25393] Adding new function from_csv()
- [SPARK-21291] 在資料框架中新增 R partitionBy API[SPARK-21291] add R partitionBy API in DataFrame
- [SPARK-25007] 將 array_intersect/array_except/array_union/shuffle 新增至 SparkR[SPARK-25007] Add array_intersect/array_except/array_union/shuffle to SparkR
- [SPARK-25234] 避免平行處理中的整數溢位[SPARK-25234] avoid integer overflow in parallelize
- [SPARK-25117] 在 R 中新增 ALL 和 INTERSECT 所有支援[SPARK-25117] Add EXCEPT ALL and INTERSECT ALL support in R
- [SPARK-24537] 新增 array_remove/array_zip/map_from_arrays/array_distinct[SPARK-24537] Add array_remove / array_zip / map_from_arrays / array_distinct
- [SPARK-24187] 將 array_join 函數新增至 SparkR[SPARK-24187] Add array_join function to SparkR
- [SPARK-24331] 新增 arrays_overlap、array_repeat map_entries 至 SparkR[SPARK-24331] Adding arrays_overlap, array_repeat, map_entries to SparkR
- [SPARK-24198] 將配量函數新增至 SparkR[SPARK-24198] Adding slice function to SparkR
- [SPARK-24197] 將 array_sort 函數新增至 SparkR[SPARK-24197] Adding array_sort function to SparkR
- [SPARK-24185] 將壓平合併函式新增至 SparkR[SPARK-24185] add flatten function to SparkR
- [SPARK-24069] 新增 array_min/array_max 函數[SPARK-24069] Add array_min / array_max functions
- [SPARK-24054] 新增 array_position 函式/element_at 函數[SPARK-24054] Add array_position function / element_at functions
- [SPARK-23770] 在 SparkR 中新增 repartitionByRange API[SPARK-23770] Add repartitionByRange API in SparkR
程式設計手冊: SparkR Spark) 上的 (R 。Programming guide: SparkR (R on Spark).
GraphXGraphX
- [SPARK-25268] 執行平行個人化 PageRank 擲回序列化例外狀況[SPARK-25268] run Parallel Personalized PageRank throws serialization Exception
程式設計手冊: GraphX 程式設計手冊。Programming guide: GraphX Programming Guide.
棄用功能Deprecations
- [SPARK-23451] 取代 KMeans computeCost[SPARK-23451] Deprecate KMeans computeCost
- [SPARK-25345] 從 ImageSchema 取代 readImages Api[SPARK-25345] Deprecate readImages APIs from ImageSchema
行為的變更Changes of behavior
- [SPARK-23549] 在比較 timestamp 與 date 時轉換為 timestamp[SPARK-23549] Cast to timestamp when comparing timestamp with date
- [SPARK-24324] pandas 分組的地圖 UDF 應依名稱指派結果資料行[SPARK-24324] pandas Grouped Map UDF should assign result columns by name
- [SPARK-25088] Rest 伺服器預設 & 檔更新[SPARK-25088] Rest Server default & doc updates
- [SPARK-23425] 使用萬用字元的 hdfs 檔案路徑載入資料無法正常運作[SPARK-23425] load data for hdfs file path with wildcard usage is not working properly
- [SPARK-23173] from_json 可以為標示為不可為 null 的欄位產生 null[SPARK-23173] from_json can produce nulls for fields which are marked as non-nullable
- [SPARK-24966] 執行設定作業的優先順序規則[SPARK-24966] Implement precedence rules for set operations
- [SPARK-25708] 擁有不含 GROUP BY 的應該是全域匯總[SPARK-25708] HAVING without GROUP BY should be global aggregate
- [SPARK-24341] 在子查詢中正確處理多重值[SPARK-24341] Correctly handle multi-value IN subquery
- [SPARK-19724] 建立具有已存在預設位置的 managed 資料表應該會擲回例外狀況[SPARK-19724] Create a managed table with an existed default location should throw an exception
請參閱所有行為變更的 遷移指南 。See the Migration Guide for all behavior changes.
已知問題Known Issues
- [SPARK-25793] 在 BisectingKMeans 中載入模型 bug[SPARK-25793] Loading model bug in BisectingKMeans
- [SPARK-25271] CTAS 與 Hive parquet 資料表應該利用原生 parquet 來源[SPARK-25271] CTAS with Hive parquet tables should leverage native parquet source
- [SPARK-24935] 從 Spark 2.2 執行 Hive UDAF 的問題[SPARK-24935] Problem with Executing Hive UDAF’s from Spark 2.2 Onwards
維護更新Maintenance Updates
請參閱 Databricks Runtime 5.0 維護更新。See Databricks Runtime 5.0 maintenance updates.
系統內容System Environment
- 作業系統: UBUNTU 16.04.5 LTSOperating System: Ubuntu 16.04.5 LTS
- JAVA: 1.8.0 _162Java: 1.8.0_162
- Scala:2.11。8Scala: 2.11.8
- Python:適用 于 python 3 叢集的 python 2 叢集和3.5.2 的2.7.12。Python: 2.7.12 for Python 2 clusters and 3.5.2 for Python 3 clusters. 如需詳細資訊,請參閱 Python 版本。For details, see Python version.
- R: r 版本 3.4.4 (2018-03-15) R: R version 3.4.4 (2018-03-15)
- GPU 叢集:已安裝下列 NVIDIA GPU 程式庫:GPU clusters: The following NVIDIA GPU libraries are installed:
- Tesla 驅動程式375.66Tesla driver 375.66
- CUDA 9。0CUDA 9.0
- cuDNN 7。0cuDNN 7.0
注意
雖然 Apache Spark 2.4 支援 Scala 2.12,但 Databricks Runtime 5.0 並不支援。Although Scala 2.12 is supported in Apache Spark 2.4, it is not supported in Databricks Runtime 5.0.
已安裝 Python 程式庫Installed Python Libraries
程式庫Library | 版本Version | 程式庫Library | 版本Version | 程式庫Library | 版本Version |
---|---|---|---|---|---|
ansi2htmlansi2html | 1.1.11.1.1 | argparseargparse | 1.2.11.2.1 | 反向移植-abcbackports-abc | 0.50.5 |
botoboto | 2.42.02.42.0 | boto3boto3 | 1.4.11.4.1 | botocorebotocore | 1.4.701.4.70 |
brewer2mplbrewer2mpl | 1.4.11.4.1 | certificertifi | 2016.2.282016.2.28 | cfficffi | 1.7.01.7.0 |
chardetchardet | 2.3.02.3.0 | coloramacolorama | 0.3.70.3.7 | configobjconfigobj | 5.0.65.0.6 |
密碼編譯cryptography | 1.51.5 | cyclercycler | 0.10.00.10.0 | CythonCython | 0.24.10.24.1 |
裝飾decorator | 4.0.104.0.10 | docutilsdocutils | 0.140.14 | enum34enum34 | 1.1.61.1.6 |
et-xmlfileet-xmlfile | 1.0.11.0.1 | freetype-.pyfreetype-py | 1.0.21.0.2 | funcsigsfuncsigs | 1.0.21.0.2 |
fusepyfusepy | 2.0.42.0.4 | 未來futures | 3.2.03.2.0 | ggplotggplot | 0.6.80.6.8 |
html5libhtml5lib | 0.9990.999 | idnaidna | 2.12.1 | 址ipaddress | 1.0.161.0.16 |
ipythonipython | 2.2.02.2.0 | ipython-genutilsipython-genutils | 0.1.00.1.0 | jdcaljdcal | 1.21.2 |
Jinja2Jinja2 | 2.82.8 | jmespathjmespath | 0.9.00.9.0 | llvmlitellvmlite | 0.13.00.13.0 |
lxmllxml | 3.6.43.6.4 | MarkupSafeMarkupSafe | 0.230.23 | matplotlibmatplotlib | 1.5.31.5.3 |
mpld3mpld3 | 0.20.2 | msgpack-pythonmsgpack-python | 0.4.70.4.7 | ndg-HTTPsclientndg-httpsclient | 0.3.30.3.3 |
numbanumba | 0.28.10.28.1 | numpynumpy | 1.11.11.11.1 | openpyxlopenpyxl | 2.3.22.3.2 |
pandaspandas | 0.19.20.19.2 | pathlib2pathlib2 | 2.1.02.1.0 | 佩西patsy | 0.4.10.4.1 |
pexpectpexpect | 4.0.14.0.1 | picklesharepickleshare | 0.7.40.7.4 | 枕頭Pillow | 3.3.13.3.1 |
pippip | 18.018.0 | 層ply | 3.93.9 | 提示-工具組prompt-toolkit | 1.0.71.0.7 |
psycopg2psycopg2 | 2.6.22.6.2 | ptyprocessptyprocess | 0.5.10.5.1 | py4jpy4j | 0.10.30.10.3 |
pyarrowpyarrow | 0.8.00.8.0 | pyasn1pyasn1 | 0.1.90.1.9 | pycparserpycparser | 2.142.14 |
PygmentsPygments | 2.1.32.1.3 | PyGObjectPyGObject | 3.20.03.20.0 | pyOpenSSLpyOpenSSL | 16.0.016.0.0 |
pyparsingpyparsing | 2.2.02.2.0 | pypngpypng | 0.0.180.0.18 | PythonPython | 2.7.122.7.12 |
python-dateutilpython-dateutil | 2.5.32.5.3 | python-geohashpython-geohash | 0.8.50.8.5 | pytzpytz | 2016.6.12016.6.1 |
requestsrequests | 2.11.12.11.1 | s3transfers3transfer | 0.1.90.1.9 | scikit-learnscikit-learn | 0.18.10.18.1 |
scipyscipy | 0.18.10.18.1 | 沖刷scour | 0.320.32 | 以 seabornseaborn | 0.7.10.7.1 |
setuptoolssetuptools | 40.4.140.4.1 | simplejsonsimplejson | 3.8.23.8.2 | simples3simples3 | 1.01.0 |
singledispatchsingledispatch | 3.4.0.33.4.0.3 | 六six | 1.10.01.10.0 | statsmodelsstatsmodels | 0.6.10.6.1 |
龍捲風tornado | 5.1.15.1.1 | traitletstraitlets | 4.3.04.3.0 | urllib3urllib3 | 1.19.11.19.1 |
virtualenvvirtualenv | 15.0.115.0.1 | wcwidthwcwidth | 0.1.70.1.7 | wheelwheel | 0.31.10.31.1 |
wsgirefwsgiref | 0.1.20.1.2 |
已安裝的 R 程式庫Installed R Libraries
程式庫Library | 版本Version | 程式庫Library | 版本Version | 程式庫Library | 版本Version |
---|---|---|---|---|---|
abindabind | 1.4-51.4-5 | assertthatassertthat | 0.2.00.2.0 | backportsbackports | 1.1.21.1.2 |
basebase | 3.4.43.4.4 | base64encbase64enc | 0.1-30.1-3 | BHBH | 1.66.0-11.66.0-1 |
bindrbindr | 0.1.10.1.1 | bindrcppbindrcpp | 0.2.20.2.2 | bitbit | 1.1-141.1-14 |
bit64bit64 | 0.9-70.9-7 | bitopsbitops | 1.0-61.0-6 | blobblob | 1.1.11.1.1 |
bootboot | 1.3-201.3-20 | brewbrew | 1.0-61.0-6 | broombroom | 0.5.00.5.0 |
callrcallr | 3.0.03.0.0 | carcar | 3.0-23.0-2 | carDatacarData | 3.0-13.0-1 |
caretcaret | 6.0-806.0-80 | cellrangercellranger | 1.1.01.1.0 | chronchron | 2.3-522.3-52 |
classclass | 7.3-147.3-14 | clicli | 1.0.01.0.0 | 叢集cluster | 2.0.7-12.0.7-1 |
codetoolscodetools | 0.2-150.2-15 | colorspacecolorspace | 1.3-21.3-2 | commonmarkcommonmark | 1.51.5 |
compilercompiler | 3.4.43.4.4 | crayoncrayon | 1.3.41.3.4 | curlcurl | 3.23.2 |
CVSTCVST | 0.2-20.2-2 | data.tabledata.table | 1.11.41.11.4 | datasetsdatasets | 3.4.43.4.4 |
DBIDBI | 1.0.01.0.0 | ddalphaddalpha | 1.3.41.3.4 | DEoptimRDEoptimR | 1.0-81.0-8 |
descdesc | 1.2.01.2.0 | devtoolsdevtools | 1.13.61.13.6 | digestdigest | 0.6.160.6.16 |
dimReddimRed | 0.1.00.1.0 | doMCdoMC | 1.3.51.3.5 | dplyrdplyr | 0.7.60.7.6 |
DRRDRR | 0.0.30.0.3 | fansifansi | 0.3.00.3.0 | forcatsforcats | 0.3.00.3.0 |
foreachforeach | 1.4.41.4.4 | foreignforeign | 0.8-700.8-70 | gbmgbm | 2.1.32.1.3 |
幾何geometry | 0.3-60.3-6 | ggplot2ggplot2 | 3.0.03.0.0 | git2rgit2r | 0.23.00.23.0 |
glmnetglmnet | 2.0-162.0-16 | glueglue | 1.3.01.3.0 | gowergower | 0.1.20.1.2 |
graphicsgraphics | 3.4.43.4.4 | grDevicesgrDevices | 3.4.43.4.4 | gridgrid | 3.4.43.4.4 |
gsubfngsubfn | 0.70.7 | gtablegtable | 0.2.00.2.0 | H2oh2o | 3.20.0.23.20.0.2 |
havenhaven | 1.1.21.1.2 | hmshms | 0.4.20.4.2 | httrhttr | 1.3.11.3.1 |
hwriterhwriter | 1.3.21.3.2 | hwriterPlushwriterPlus | 1.0-31.0-3 | ipredipred | 0.9-70.9-7 |
iteratorsiterators | 1.0.101.0.10 | jsonlitejsonlite | 1.51.5 | kernlabkernlab | 0.9-270.9-27 |
KernSmoothKernSmooth | 2.23-152.23-15 | labelinglabeling | 0.30.3 | latticelattice | 0.20-350.20-35 |
lavalava | 1.6.31.6.3 | lazyevallazyeval | 0.2.10.2.1 | littlerlittler | 0.3.40.3.4 |
lme4lme4 | 1.1-18-11.1-18-1 | lubridatelubridate | "1.7.4 | magicmagic | 1.5-81.5-8 |
magrittrmagrittr | 1.51.5 | mapprojmapproj | 1.2.61.2.6 | mapsmaps | 3.3.03.3.0 |
maptoolsmaptools | 0.9-30.9-3 | MASSMASS | 7.3-507.3-50 | MatrixMatrix | 1.2-141.2-14 |
MatrixModelsMatrixModels | 0.4-10.4-1 | memoisememoise | 1.1.01.1.0 | methodsmethods | 3.4.43.4.4 |
mgcvmgcv | 1.8-241.8-24 | mimemime | 0.50.5 | minqaminqa | 1.2.41.2.4 |
ModelMetricsModelMetrics | 1.2.01.2.0 | munsellmunsell | 0.5.00.5.0 | mvtnormmvtnorm | 1.0-81.0-8 |
nlmenlme | 3.1-1373.1-137 | nloptrnloptr | 1.0.41.0.4 | nnetnnet | 7.3-127.3-12 |
numDerivnumDeriv | 2016.8-12016.8-1 | opensslopenssl | 1.0.21.0.2 | openxlsxopenxlsx | 4.1.04.1.0 |
parallelparallel | 3.4.43.4.4 | pbkrtestpbkrtest | 0.4-70.4-7 | pillarpillar | 1.3.01.3.0 |
pkgbuildpkgbuild | 1.0.01.0.0 | pkgconfigpkgconfig | 2.0.22.0.2 | pkgKittenpkgKitten | 0.1.40.1.4 |
pkgloadpkgload | 1.0.01.0.0 | plogrplogr | 0.2.00.2.0 | plspls | 2.7-02.7-0 |
plyrplyr | 1.8.41.8.4 | praisepraise | 1.0.01.0.0 | prettyunitsprettyunits | 1.0.21.0.2 |
pROCpROC | 1.12.11.12.1 | processxprocessx | 3.2.03.2.0 | prodlimprodlim | 2018.04.182018.04.18 |
protoproto | 1.0.01.0.0 | psps | 1.1.01.1.0 | purrrpurrr | 0.2.50.2.5 |
quantregquantreg | 5.365.36 | R.methodsS3R.methodsS3 | 1.7.11.7.1 | R.ooR.oo | 1.22.01.22.0 |
R.utilsR.utils | 2.7.02.7.0 | R6R6 | 2.2.22.2.2 | randomForestrandomForest | 4.6-144.6-14 |
RColorBrewerRColorBrewer | 1.1-21.1-2 | RcppRcpp | 0.12.180.12.18 | RcppEigenRcppEigen | 0.3.3.4.00.3.3.4.0 |
RcppRollRcppRoll | 0.3.00.3.0 | RCurlRCurl | 1.95-4.111.95-4.11 | readrreadr | 1.1.11.1.1 |
readxlreadxl | 1.1.01.1.0 | recipesrecipes | 0.1.30.1.3 | rematchrematch | 1.0.11.0.1 |
reshape2reshape2 | 1.4.31.4.3 | 力拓rio | 0.5.10 版0.5.10 | rlangrlang | 0.2.20.2.2 |
robustbaserobustbase | 0.93-20.93-2 | RODBCRODBC | 1.3-151.3-15 | roxygen2roxygen2 | 6.1.06.1.0 |
rpartrpart | 4.1-134.1-13 | rprojrootrprojroot | 1.3-21.3-2 | RserveRserve | 1.7-31.7-3 |
RSQLiteRSQLite | 2.1.12.1.1 | rstudioapirstudioapi | 0.70.7 | scalesscales | 1.0.01.0.0 |
sfsmiscsfsmisc | 1.1-21.1-2 | spsp | 1.3-11.3-1 | SparkRSparkR | 2.4.02.4.0 |
SparseMSparseM | 1.771.77 | spatialspatial | 7.3-117.3-11 | splinessplines | 3.4.43.4.4 |
sqldfsqldf | 0.4-110.4-11 | SQUAREMSQUAREM | 2017.10-12017.10-1 | statmodstatmod | 1.4.301.4.30 |
statsstats | 3.4.43.4.4 | stats4stats4 | 3.4.43.4.4 | stringistringi | 1.2.41.2.4 |
stringrstringr | 1.3.11.3.1 | survivalsurvival | 2.42-62.42-6 | tcltktcltk | 3.4.43.4.4 |
TeachingDemosTeachingDemos | 2.102.10 | testthattestthat | 2.0.02.0.0 | tibbletibble | 1.4.21.4.2 |
tidyrtidyr | 0.8.10.8.1 | tidyselecttidyselect | 0.2.40.2.4 | timeDatetimeDate | 3043.1023043.102 |
toolstools | 3.4.43.4.4 | utf8utf8 | 1.1.41.1.4 | utilsutils | 3.4.43.4.4 |
viridisLiteviridisLite | 0.3.00.3.0 | whiskerwhisker | 0.3-20.3-2 | withrwithr | 2.1.22.1.2 |
xml2xml2 | 1.2.01.2.0 | zipzip | 1.0.01.0.0 |
已安裝 JAVA 和 Scala 程式庫 (Scala 2.11 叢集版本) Installed Java and Scala libraries (Scala 2.11 cluster version)
群組識別碼Group ID | 成品識別碼Artifact ID | 版本Version |
---|---|---|
antlrantlr | antlrantlr | 2.7.72.7.7 |
amazonawscom.amazonaws | amazon-kinesis-用戶端amazon-kinesis-client | 1.8.101.8.10 |
amazonawscom.amazonaws | aws-java-sdk-自動調整aws-java-sdk-autoscaling | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-cloudformationaws-java-sdk-cloudformation | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-cloudfrontaws-java-sdk-cloudfront | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-cloudhsmaws-java-sdk-cloudhsm | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-cloudsearchaws-java-sdk-cloudsearch | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-cloudtrailaws-java-sdk-cloudtrail | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-cloudwatchaws-java-sdk-cloudwatch | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-cloudwatchmetricsaws-java-sdk-cloudwatchmetrics | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-codedeployaws-java-sdk-codedeploy | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-cognitoidentityaws-java-sdk-cognitoidentity | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-cognitosyncaws-java-sdk-cognitosync | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-configaws-java-sdk-config | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-核心aws-java-sdk-core | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-datapipelineaws-java-sdk-datapipeline | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-directconnectaws-java-sdk-directconnect | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-目錄aws-java-sdk-directory | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-dynamodbaws-java-sdk-dynamodb | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-ec2aws-java-sdk-ec2 | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-ecsaws-java-sdk-ecs | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-efsaws-java-sdk-efs | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-elasticacheaws-java-sdk-elasticache | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-elasticbeanstalkaws-java-sdk-elasticbeanstalk | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-elasticloadbalancingaws-java-sdk-elasticloadbalancing | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-elastictranscoderaws-java-sdk-elastictranscoder | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-emraws-java-sdk-emr | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-glacieraws-java-sdk-glacier | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-iamaws-java-sdk-iam | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-microsoft.importexportaws-java-sdk-importexport | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-kinesisaws-java-sdk-kinesis | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-kmsaws-java-sdk-kms | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-lambdaaws-java-sdk-lambda | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-記錄aws-java-sdk-logs | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-machinelearningaws-java-sdk-machinelearning | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-opsworksaws-java-sdk-opsworks | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-rdsaws-java-sdk-rds | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-redshiftaws-java-sdk-redshift | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-route53aws-java-sdk-route53 | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-s3aws-java-sdk-s3 | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-sesaws-java-sdk-ses | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-simpledbaws-java-sdk-simpledb | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-simpleworkflowaws-java-sdk-simpleworkflow | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-snsaws-java-sdk-sns | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-sqsaws-java-sdk-sqs | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-ssmaws-java-sdk-ssm | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-storagegatewayaws-java-sdk-storagegateway | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-stsaws-java-sdk-sts | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-支援aws-java-sdk-support | 1.11.3131.11.313 |
amazonawscom.amazonaws | aws-java-sdk-swf-程式庫aws-java-sdk-swf-libraries | 1.11.221.11.22 |
amazonawscom.amazonaws | aws-java-sdk-工作區aws-java-sdk-workspaces | 1.11.3131.11.313 |
amazonawscom.amazonaws | jmespath-javajmespath-java | 1.11.3131.11.313 |
carrotsearchcom.carrotsearch | hppchppc | 0.7.20.7.2 |
chuusaicom.chuusai | shapeless_2 11shapeless_2.11 | 2.3.22.3.2 |
clearspring。com.clearspring.analytics | 資料流stream | 2.7.02.7.0 |
databrickscom.databricks | RserveRserve | 1.8-31.8-3 |
databrickscom.databricks | dbml-local_2 11dbml-local_2.11 | 0.5.0-db7-spark 2。40.5.0-db7-spark2.4 |
databrickscom.databricks | dbml-local_2 11-測試dbml-local_2.11-tests | 0.5.0-db7-spark 2。40.5.0-db7-spark2.4 |
databrickscom.databricks | jets3tjets3t | 0.7.1-00.7.1-0 |
databricks. scalapbcom.databricks.scalapb | compilerplugin_2 11compilerplugin_2.11 | 0.4.15-90.4.15-9 |
databricks. scalapbcom.databricks.scalapb | scalapb-runtime_2 11scalapb-runtime_2.11 | 0.4.15-90.4.15-9 |
esotericsoftwarecom.esotericsoftware | kryo-陰影kryo-shaded | 4.0.24.0.2 |
esotericsoftwarecom.esotericsoftware | minlogminlog | 1.3.01.3.0 |
而將 com.fasterxml.jackson.corecom.fasterxml | 同學classmate | 1.0.01.0.0 |
而將 com.fasterxml.jackson.core. jackson corecom.fasterxml.jackson.core | jackson-批註jackson-annotations | 2.6.72.6.7 |
而將 com.fasterxml.jackson.core. jackson corecom.fasterxml.jackson.core | jackson-核心jackson-core | 2.6.72.6.7 |
而將 com.fasterxml.jackson.core. jackson corecom.fasterxml.jackson.core | jackson-databindjackson-databind | 2.6.7.12.6.7.1 |
而將 com.fasterxml.jackson.core. jackson. dataformatcom.fasterxml.jackson.dataformat | jackson-dataformat-cborjackson-dataformat-cbor | 2.6.72.6.7 |
而將 com.fasterxml.jackson.core. jackson. 資料類型com.fasterxml.jackson.datatype | jackson-datatype-joda-timejackson-datatype-joda | 2.6.72.6.7 |
而將 com.fasterxml.jackson.core. jackson. modulecom.fasterxml.jackson.module | jackson-module-paranamerjackson-module-paranamer | 2.6.72.6.7 |
而將 com.fasterxml.jackson.core. jackson. modulecom.fasterxml.jackson.module | jackson-module-scala_2 11jackson-module-scala_2.11 | 2.6.7.12.6.7.1 |
fommilcom.github.fommil | jniloaderjniloader | 1.11.1 |
fommil. netlibcom.github.fommil.netlib | corecore | 1.1.21.1.2 |
fommil. netlibcom.github.fommil.netlib | native_ref-javanative_ref-java | 1.11.1 |
fommil. netlibcom.github.fommil.netlib | native_ref-java-原生native_ref-java-natives | 1.11.1 |
fommil. netlibcom.github.fommil.netlib | native_system-javanative_system-java | 1.11.1 |
fommil. netlibcom.github.fommil.netlib | native_system-java-原生native_system-java-natives | 1.11.1 |
fommil. netlibcom.github.fommil.netlib | netlib-native_ref-linux-x86_64-原生netlib-native_ref-linux-x86_64-natives | 1.11.1 |
fommil. netlibcom.github.fommil.netlib | netlib-native_system-linux-x86_64-原生netlib-native_system-linux-x86_64-natives | 1.11.1 |
lubencom.github.luben | zstd-jnizstd-jni | 1.3.2-21.3.2-2 |
rwlcom.github.rwl | jtransformsjtransforms | 2.4.02.4.0 |
findbugs。com.google.code.findbugs | jsr305jsr305 | 2.0.12.0.1 |
gson。com.google.code.gson | gsongson | 2.2.42.2.4 |
guavacom.google.guava | 番 石榴guava | 15.015.0 |
protobufcom.google.protobuf | protobuf-javaprotobuf-java | 2.6.12.6.1 |
googlecode. javaewahcom.googlecode.javaewah | JavaEWAHJavaEWAH | 0.3.20.3.2 |
h2databasecom.h2database | h2h2 | 1.3.1741.3.174 |
jcraftcom.jcraft | jschjsch | 0.1.500.1.50 |
jolboxcom.jolbox | bonecpbonecp | 0.8.0 版版0.8.0.RELEASE |
mchangecom.mchange | c3p0c3p0 | 0.9.5.10.9.5.1 |
mchangecom.mchange | mchange-commons-javamchange-commons-java | 0.2.100.2.10 |
com.microsoft.azurecom.microsoft.azure | azure-data-lake-store-sdkazure-data-lake-store-sdk | 2.2.82.2.8 |
.comcom.microsoft.sqlserver | mssql-jdbcmssql-jdbc | 6.2.2. jre86.2.2.jre8 |
ningcom.ning | 壓縮-lzfcompress-lzf | 1.0.31.0.3 |
.com. mailcom.sun.mail | javax.xml.transform.dom.domresultjavax.mail | 1.5.21.5.2 |
thoughtworks. paranamercom.thoughtworks.paranamer | paranamerparanamer | 2.82.8 |
trueaccord. 鏡頭com.trueaccord.lenses | lenses_2 11lenses_2.11 | 0.30.3 |
.comcom.twitter | 冷藏-javachill-java | 0.9.30.9.3 |
.comcom.twitter | chill_2 11chill_2.11 | 0.9.30.9.3 |
.comcom.twitter | parquet-hadoop-套件組合parquet-hadoop-bundle | 1.6.01.6.0 |
.comcom.twitter | util-app_2 11util-app_2.11 | 6.23.06.23.0 |
.comcom.twitter | util-core_2 11util-core_2.11 | 6.23.06.23.0 |
.comcom.twitter | util-jvm_2 11util-jvm_2.11 | 6.23.06.23.0 |
typesafecom.typesafe | configconfig | 1.2.11.2.1 |
typesafe。 scala-記錄com.typesafe.scala-logging | scala-記錄-api_2 11scala-logging-api_2.11 | 2.1.22.1.2 |
typesafe。 scala-記錄com.typesafe.scala-logging | scala-記錄-slf4j_2 11scala-logging-slf4j_2.11 | 2.1.22.1.2 |
univocitycom.univocity | univocity-剖析器univocity-parsers | 2.7.32.7.3 |
vlkancom.vlkan | flatbuffersflatbuffers | 1.2.0-3f79e0551.2.0-3f79e055 |
zaxxercom.zaxxer | HikariCPHikariCP | 3.1.03.1.0 |
commons-beanutilscommons-beanutils | commons-beanutilscommons-beanutils | 1.7.01.7.0 |
commons-beanutilscommons-beanutils | commons-beanutils-核心commons-beanutils-core | 1.8.01.8.0 |
commons-clicommons-cli | commons-clicommons-cli | 1.21.2 |
commons-codec.jarcommons-codec | commons-codec.jarcommons-codec | 1.101.10 |
commons-集合commons-collections | commons-集合commons-collections | 3.2.23.2.2 |
commons-設定commons-configuration | commons-設定commons-configuration | 1.61.6 |
commons-dbcpcommons-dbcp | commons-dbcpcommons-dbcp | 1.41.4 |
commons-digestercommons-digester | commons-digestercommons-digester | 1.81.8 |
commons-HTTPclientcommons-httpclient | commons-HTTPclientcommons-httpclient | 3.13.1 |
commons-iocommons-io | commons-iocommons-io | 2.42.4 |
commons-langcommons-lang | commons-langcommons-lang | 2.62.6 |
commons-記錄commons-logging | commons-記錄commons-logging | 1.1.31.1.3 |
commons-netcommons-net | commons-netcommons-net | 3.13.1 |
commons 集區commons-pool | commons 集區commons-pool | 1.5.41.5.4 |
資訊. ganglia. gmetric4jinfo.ganglia.gmetric4j | gmetric4jgmetric4j | 1.0.71.0.7 |
airliftio.airlift | aircompressoraircompressor | 0.100.10 |
dropwizard。計量io.dropwizard.metrics | 計量-核心metrics-core | 版3.1.5 |
dropwizard。計量io.dropwizard.metrics | 計量-gangliametrics-ganglia | 版3.1.5 |
dropwizard。計量io.dropwizard.metrics | 計量-graphitemetrics-graphite | 版3.1.5 |
dropwizard。計量io.dropwizard.metrics | 計量-healthchecksmetrics-healthchecks | 版3.1.5 |
dropwizard。計量io.dropwizard.metrics | 計量-jetty9metrics-jetty9 | 版3.1.5 |
dropwizard。計量io.dropwizard.metrics | 計量-jsonmetrics-json | 版3.1.5 |
dropwizard。計量io.dropwizard.metrics | 計量-jvmmetrics-jvm | 版3.1.5 |
dropwizard。計量io.dropwizard.metrics | 計量-log4jmetrics-log4j | 版3.1.5 |
dropwizard。計量io.dropwizard.metrics | 計量-servletmetrics-servlets | 版3.1.5 |
nettyio.netty | nettynetty | 3.9.9。最終3.9.9.Final |
nettyio.netty | netty-全部netty-all | 4.1.17。最終4.1.17.Final |
prometheusio.prometheus | simpleclientsimpleclient | 0.0.160.0.16 |
prometheusio.prometheus | simpleclient_commonsimpleclient_common | 0.0.160.0.16 |
prometheusio.prometheus | simpleclient_dropwizardsimpleclient_dropwizard | 0.0.160.0.16 |
prometheusio.prometheus | simpleclient_servletsimpleclient_servlet | 0.0.160.0.16 |
prometheus。io.prometheus.jmx | 收集器collector | 0.70.7 |
javax.xml.transform.dom.domresult。啟用javax.activation | activationactivation | 1.1.11.1.1 |
javax.xml.transform.dom.domresult。注釋javax.annotation | javax.xml.transform.dom.domresult. 注釋-apijavax.annotation-api | 1.21.2 |
javax.xml.transform.dom.domresultjavax.el | javax.xml.transform.dom.domresult-apijavax.el-api | 2.2.42.2.4 |
javax.xml.transform.dom.domresult. jdojavax.jdo | jdo-apijdo-api | 3.0.13.0.1 |
javax.xml.transform.dom.domresult servletjavax.servlet | javax.xml.transform.dom.domresult-apijavax.servlet-api | 3.1.03.1.0 |
javax.servlet.jspjavax.servlet.jsp | jsp-apijsp-api | 2.12.1 |
javax.xml.transform.dom.domresult 交易javax.transaction | jtajta | 1.11.1 |
javax.xml.transform.dom.domresult。驗證javax.validation | 驗證-apivalidation-api | 1.1.0。最終1.1.0.Final |
javax.ws.rsjavax.ws.rs | javax.ws.rs-apijavax.ws.rs-api | 2.0.12.0.1 |
javax.xml bindjavax.xml.bind | jaxb-apijaxb-api | 2.2.22.2.2 |
javax.xml 資料流程javax.xml.stream | stax-apistax-api | 1.0-21.0-2 |
javolutionjavolution | javolutionjavolution | 5.5.15.5.1 |
jlinejline | jlinejline | 2.112.11 |
joda-time 時間joda-time | joda-time 時間joda-time | 2.9.32.9.3 |
Log4jlog4j | apache-log4j-額外專案apache-log4j-extras | 1.2.171.2.17 |
Log4jlog4j | Log4jlog4j | 1.2.171.2.17 |
hydromaticnet.hydromatic | eigenbase-propertieseigenbase-properties | 1.1.51.1.5 |
razorvinenet.razorvine | pyrolitepyrolite | 4.134.13 |
jpamnet.sf.jpam | jpamjpam | 1.11.1 |
opencsvnet.sf.opencsv | opencsvopencsv | 2.32.3 |
supercsvnet.sf.supercsv | super-csvsuper-csv | 2.2.02.2.0 |
net.tcpnet.snowflake | 雪花式-jdbcsnowflake-jdbc | 3.6.33.6.3 |
net.tcpnet.snowflake | spark-snowflake_2 11spark-snowflake_2.11 | 2.4.12.4.1 |
sourceforge. f2jnet.sourceforge.f2j | arpack_combined_allarpack_combined_all | 0.10.1 |
acpltorg.acplt | oncrpconcrpc | 1.0.71.0.7 |
antlrorg.antlr | ST4ST4 | 4.0.44.0.4 |
antlrorg.antlr | antlr-執行時間antlr-runtime | 3.43.4 |
antlrorg.antlr | antlr4-執行時間antlr4-runtime | 4.74.7 |
antlrorg.antlr | stringtemplatestringtemplate | 3.2.13.2.1 |
apache. antorg.apache.ant | antant | 1.9.21.9.2 |
apache. antorg.apache.ant | ant-jschant-jsch | 1.9.21.9.2 |
apache. antorg.apache.ant | ant-launcherant-launcher | 1.9.21.9.2 |
org. 箭號org.apache.arrow | 箭號-格式arrow-format | 0.10.00.10.0 |
org. 箭號org.apache.arrow | 箭號-記憶體arrow-memory | 0.10.00.10.0 |
org. 箭號org.apache.arrow | 箭號-向量arrow-vector | 0.10.00.10.0 |
apache. avroorg.apache.avro | avroavro | 1.8.21.8.2 |
apache. avroorg.apache.avro | avro-ipcavro-ipc | 1.8.21.8.2 |
apache. avroorg.apache.avro | avro-mapred-hadoop2avro-mapred-hadoop2 | 1.8.21.8.2 |
calciteorg.apache.calcite | calcite-avaticacalcite-avatica | 1.2.0-發展1.2.0-incubating |
calciteorg.apache.calcite | calcite-核心calcite-core | 1.2.0-發展1.2.0-incubating |
calciteorg.apache.calcite | calcite-linq4jcalcite-linq4j | 1.2.0-發展1.2.0-incubating |
commonsorg.apache.commons | commons-壓縮commons-compress | 1.8.11.8.1 |
commonsorg.apache.commons | commons-加密commons-crypto | 1.0.01.0.0 |
commonsorg.apache.commons | commons-lang3commons-lang3 | 3.53.5 |
commonsorg.apache.commons | commons-math3commons-math3 | 3.4.13.4.1 |
編者org.apache.curator | 編者-用戶端curator-client | 2.7.12.7.1 |
編者org.apache.curator | 編者-架構curator-framework | 2.7.12.7.1 |
編者org.apache.curator | 編者-食譜curator-recipes | 2.7.12.7.1 |
derbyorg.apache.derby | Derbyderby | 10.12.1.110.12.1.1 |
org. apiorg.apache.directory.api | api-asn1-apiapi-asn1-api | 1.0.0-M201.0.0-M20 |
org. apiorg.apache.directory.api | api-utilapi-util | 1.0.0-M201.0.0-M20 |
目錄. 伺服器org.apache.directory.server | apacheds-國際化apacheds-i18n | 2.0.0-M152.0.0-M15 |
目錄. 伺服器org.apache.directory.server | apacheds-kerberos-編解碼器apacheds-kerberos-codec | 2.0.0-M152.0.0-M15 |
apache. hadooporg.apache.hadoop | hadoop-批註hadoop-annotations | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-驗證hadoop-auth | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-用戶端hadoop-client | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-通用hadoop-common | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-hdfshadoop-hdfs | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-mapreduce-用戶端應用程式hadoop-mapreduce-client-app | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-mapreduce-用戶端-通用hadoop-mapreduce-client-common | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-mapreduce-用戶端-核心hadoop-mapreduce-client-core | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-mapreduce-用戶端-jobclient.closehadoop-mapreduce-client-jobclient | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-mapreduce-用戶端隨機hadoop-mapreduce-client-shuffle | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-yarn-apihadoop-yarn-api | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-yarn-用戶端hadoop-yarn-client | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-yarn-通用hadoop-yarn-common | 2.7.32.7.3 |
apache. hadooporg.apache.hadoop | hadoop-yarn-伺服器-通用hadoop-yarn-server-common | 2.7.32.7.3 |
htraceorg.apache.htrace | htrace-核心htrace-core | 3.1.0-發展3.1.0-incubating |
org.apache.HTTPcomponentsorg.apache.httpcomponents | HTTPclienthttpclient | 4.5.44.5.4 |
org.apache.HTTPcomponentsorg.apache.httpcomponents | HTTPcorehttpcore | 4.4.84.4.8 |
ivyorg.apache.ivy | ivyivy | 2.4.02.4.0 |
orcorg.apache.orc | orc-核心-nohiveorc-core-nohive | 1.5.21.5.2 |
orcorg.apache.orc | orc-mapreduce-nohiveorc-mapreduce-nohive | 1.5.21.5.2 |
orcorg.apache.orc | orc-填充碼orc-shims | 1.5.21.5.2 |
parquetorg.apache.parquet | parquet-資料行parquet-column | 1.10.1-databricks21.10.1-databricks2 |
parquetorg.apache.parquet | parquet-通用parquet-common | 1.10.1-databricks21.10.1-databricks2 |
parquetorg.apache.parquet | parquet-編碼parquet-encoding | 1.10.1-databricks21.10.1-databricks2 |
parquetorg.apache.parquet | parquet-formatparquet-format | 2.4.02.4.0 |
parquetorg.apache.parquet | parquet-hadoopparquet-hadoop | 1.10.1-databricks21.10.1-databricks2 |
parquetorg.apache.parquet | parquet-jacksonparquet-jackson | 1.10.1-databricks21.10.1-databricks2 |
thriftorg.apache.thrift | libfb303libfb303 | 0.9.30.9.3 |
thriftorg.apache.thrift | libthriftlibthrift | 0.9.30.9.3 |
xbeanorg.apache.xbean | xbean-asm6-陰影xbean-asm6-shaded | 4.84.8 |
zookeeperorg.apache.zookeeper | zookeeperzookeeper | 3.4.63.4.6 |
codehaus. jacksonorg.codehaus.jackson | jackson-核心-asljackson-core-asl | 1.9.131.9.13 |
codehaus. jacksonorg.codehaus.jackson | jackson-jaxrsjackson-jaxrs | 1.9.131.9.13 |
codehaus. jacksonorg.codehaus.jackson | jackson-對應程式-asljackson-mapper-asl | 1.9.131.9.13 |
codehaus. jacksonorg.codehaus.jackson | jackson-xcjackson-xc | 1.9.131.9.13 |
codehaus. janinoorg.codehaus.janino | commons-compilercommons-compiler | 3.0.93.0.9 |
codehaus. janinoorg.codehaus.janino | janinojanino | 3.0.93.0.9 |
datanucleusorg.datanucleus | datanucleus-api-jdodatanucleus-api-jdo | 3.2.63.2.6 |
datanucleusorg.datanucleus | datanucleus-核心datanucleus-core | 3.2.103.2.10 |
datanucleusorg.datanucleus | datanucleus-rdbmsdatanucleus-rdbms | 3.2.93.2.9 |
jettyorg.eclipse.jetty | jetty-用戶端jetty-client | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-接續jetty-continuation | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-HTTPjetty-http | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-iojetty-io | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-jndijetty-jndi | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-加號jetty-plus | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-proxyjetty-proxy | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-安全性jetty-security | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-伺服器jetty-server | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-servletjetty-servlet | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-servletjetty-servlets | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-utiljetty-util | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-webappjetty-webapp | 9.3.20.v201705319.3.20.v20170531 |
jettyorg.eclipse.jetty | jetty-xmljetty-xml | 9.3.20.v201705319.3.20.v20170531 |
fusesource. leveldbjniorg.fusesource.leveldbjni | leveldbjni-allleveldbjni-all | 1.81.8 |
glassfish. hk2org.glassfish.hk2 | hk2-apihk2-api | 2.4.0-b342.4.0-b34 |
glassfish. hk2org.glassfish.hk2 | hk2-定位器hk2-locator | 2.4.0-b342.4.0-b34 |
glassfish. hk2org.glassfish.hk2 | hk2-公用程式hk2-utils | 2.4.0-b342.4.0-b34 |
glassfish. hk2org.glassfish.hk2 | osgi-資源-定位器osgi-resource-locator | 1.0.11.0.1 |
glassfish. hk2. externalorg.glassfish.hk2.external | aopalliance-重新封裝aopalliance-repackaged | 2.4.0-b342.4.0-b34 |
glassfish. hk2. externalorg.glassfish.hk2.external | javax.injectjavax.inject | 2.4.0-b342.4.0-b34 |
glassfish. jersey。org.glassfish.jersey.bundles.repackaged | jersey-guavajersey-guava | 2.22.22.22.2 |
glassfish. jersey 容器org.glassfish.jersey.containers | jersey-容器-servletjersey-container-servlet | 2.22.22.22.2 |
glassfish. jersey 容器org.glassfish.jersey.containers | jersey 容器-servlet-核心jersey-container-servlet-core | 2.22.22.22.2 |
glassfish. jersey coreorg.glassfish.jersey.core | jersey-clientjersey-client | 2.22.22.22.2 |
glassfish. jersey coreorg.glassfish.jersey.core | jersey-通用jersey-common | 2.22.22.22.2 |
glassfish. jersey coreorg.glassfish.jersey.core | jersey-伺服器jersey-server | 2.22.22.22.2 |
glassfish. jersey. mediaorg.glassfish.jersey.media | jersey-media-jaxbjersey-media-jaxb | 2.22.22.22.2 |
組織休眠org.hibernate | 休眠-驗證程式hibernate-validator | 5.1.1. 最終5.1.1.Final |
iq80. snappyorg.iq80.snappy | snappysnappy | 0.20.2 |
>javassistorg.javassist | >javassistjavassist | 3.18.1-GA3.18.1-GA |
jboss 記錄org.jboss.logging | jboss-記錄jboss-logging | 3.1.3.GA3.1.3.GA |
jdbiorg.jdbi | jdbijdbi | 2.63.12.63.1 |
joda-timeorg.joda | joda-time-轉換joda-convert | 1.71.7 |
joddorg.jodd | jodd-核心jodd-core | 3.5.23.5.2 |
org.json4sorg.json4s | json4s-ast_2 11json4s-ast_2.11 | 3.5.33.5.3 |
org.json4sorg.json4s | json4s-core_2 11json4s-core_2.11 | 3.5.33.5.3 |
org.json4sorg.json4s | json4s-jackson_2 11json4s-jackson_2.11 | 3.5.33.5.3 |
org.json4sorg.json4s | json4s-scalap_2 11json4s-scalap_2.11 | 3.5.33.5.3 |
lz4org.lz4 | lz4-javalz4-java | 1.4.01.4.0 |
適用于 mariadb jdbcorg.mariadb.jdbc | 適用于 mariadb-java-用戶端mariadb-java-client | 2.1.22.1.2 |
mockitoorg.mockito | mockito-全部mockito-all | 1.9.51.9.5 |
objenesisorg.objenesis | objenesisobjenesis | 2.5.12.5.1 |
于 postgresqlorg.postgresql | postgresqlpostgresql | 42.1.442.1.4 |
roaringbitmaporg.roaringbitmap | RoaringBitmapRoaringBitmap | 0.5.110.5.11 |
rocksdborg.rocksdb | rocksdbjnirocksdbjni | 5.2.15.2.1 |
rosuda. REngineorg.rosuda.REngine | REngineREngine | 2.1.02.1.0 |
scala-langorg.scala-lang | scala-compiler_2 11scala-compiler_2.11 | 2.11.82.11.8 |
scala-langorg.scala-lang | scala-library_2 11scala-library_2.11 | 2.11.82.11.8 |
scala-langorg.scala-lang | scala-reflect_2 11scala-reflect_2.11 | 2.11.82.11.8 |
scala-lang. 模組org.scala-lang.modules | scala-剖析器-combinators_2 11scala-parser-combinators_2.11 | 1.0.21.0.2 |
scala-lang. 模組org.scala-lang.modules | scala-xml_2 11scala-xml_2.11 | 1.0.51.0.5 |
scala-sbtorg.scala-sbt | 測試-介面test-interface | 1.01.0 |
scalacheckorg.scalacheck | scalacheck_2 11scalacheck_2.11 | 1.12.51.12.5 |
scalacticorg.scalactic | scalactic_2 11scalactic_2.11 | 3.0.33.0.3 |
scalanlporg.scalanlp | 輕鬆-macros_2 11breeze-macros_2.11 | 0.13.20.13.2 |
scalanlporg.scalanlp | breeze_2 11breeze_2.11 | 0.13.20.13.2 |
scalatestorg.scalatest | scalatest_2 11scalatest_2.11 | 3.0.33.0.3 |
slf4jorg.slf4j | jcl-slf4jjcl-over-slf4j | 1.7.161.7.16 |
slf4jorg.slf4j | jul-to-slf4jjul-to-slf4j | 1.7.161.7.16 |
slf4jorg.slf4j | slf4j-apislf4j-api | 1.7.161.7.16 |
slf4jorg.slf4j | slf4j-log4j12slf4j-log4j12 | 1.7.161.7.16 |
org-專案 hiveorg.spark-project.hive | hive-beelinehive-beeline | 1.2.1. spark21.2.1.spark2 |
org-專案 hiveorg.spark-project.hive | hive-clihive-cli | 1.2.1. spark21.2.1.spark2 |
org-專案 hiveorg.spark-project.hive | hive-exechive-exec | 1.2.1. spark21.2.1.spark2 |
org-專案 hiveorg.spark-project.hive | hive-jdbchive-jdbc | 1.2.1. spark21.2.1.spark2 |
org-專案 hiveorg.spark-project.hive | hive-中繼存放區hive-metastore | 1.2.1. spark21.2.1.spark2 |
的 spark-專案。 sparkorg.spark-project.spark | unusedunused | 1.0.01.0.0 |
spire-數學org.spire-math | spire-macros_2 11spire-macros_2.11 | 0.13.00.13.0 |
spire-數學org.spire-math | spire_2 11spire_2.11 | 0.13.00.13.0 |
springframeworkorg.springframework | 春季-核心spring-core | 4.1.4 版4.1.4.RELEASE |
springframeworkorg.springframework | 彈簧測試spring-test | 4.1.4 版4.1.4.RELEASE |
tukaaniorg.tukaani | xzxz | 1.51.5 |
typelevelorg.typelevel | machinist_2 11machinist_2.11 | 0.6.10.6.1 |
typelevelorg.typelevel | 宏 compat_2 11macro-compat_2.11 | 1.1.11.1.1 |
xerialorg.xerial | sqlite-jdbcsqlite-jdbc | 3.8.11.23.8.11.2 |
xerial. snappyorg.xerial.snappy | snappy-javasnappy-java | 1.1.7.11.1.7.1 |
yamlorg.yaml | snakeyamlsnakeyaml | 1.161.16 |
orooro | orooro | 2.0.82.0.8 |
software. 離子software.amazon.ion | 離子-javaion-java | 1.0.21.0.2 |
Staxstax | stax-apistax-api | 1.0.11.0.1 |
xmlencxmlenc | xmlencxmlenc | 0.520.52 |