Spark Release 2.4.0

Download img file editor for free. Games downloads - Alci's IMG Editor by Alci and many more programs are available for instant and free download. Spark Photo Editor with stickers, meme maker and the hottest filters is a true treasure for everybody! To Download Spark Photo Editor For PC,users need to install an Android Emulator like Xeplayer.With Xeplayer,you can Download Spark Photo Editor for PC version on your Windows 7,8,10 and Laptop. The 1.5 version of Alci's IMG Editor is provided as a free download on our website. Our antivirus analysis shows that this download is malware free. The tool is sometimes referred to as 'Alcis IMG Editor'. The software relates to Games. Alci's IMG Editor was developed to work on Windows 7 or Windows 8 and is compatible with 32-bit systems.

Apache Spark 2.4.0 is the fifth release in the 2.x line. This release adds Barrier Execution Mode for better integration with deep learning frameworks, introduces 30+ built-in and higher-order functions to deal with complex data type easier, improves the K8s integration, along with experimental Scala 2.12 support. Other major updates include the built-in Avro data source, Image data source, flexible streaming sinks, elimination of the 2GB block size limitation during transfer, Pandas UDF improvements. In addition, this release continues to focus on usability, stability, and polish while resolving around 1100 tickets.

To download Apache Spark 2.4.0, visit the downloads page. You can consult JIRA for the detailed changes. We have curated a list of high level changes here, grouped by major modules.

Core and Spark SQL

Major features
- Barrier Execution Mode: [SPARK-24374] Support Barrier Execution Mode in the scheduler, to better integrate with deep learning frameworks.
- Scala 2.12 Support: [SPARK-14220] Add experimental Scala 2.12 support. Now you can build Spark with Scala 2.12 and write Spark applications in Scala 2.12.
- Higher-order functions: [SPARK-23899] Add a lot of new built-in functions, including higher-order functions, to deal with complex data types easier.
- Built-in Avro data source: [SPARK-24768] Inline Spark-Avro package with logical type support, better performance and usability.
API
- [SPARK-24035] SQL syntax for Pivot
- [SPARK-24940] Coalesce and Repartition Hint for SQL Queries
- [SPARK-19602] Support column resolution of fully qualified column name
- [SPARK-21274] Implement EXCEPT ALL and INTERSECT ALL
Performance and stability
- [SPARK-16406] Reference resolution for large number of columns should be faster
- [SPARK-23486] Cache the function name from the external catalog for lookupFunctions
- [SPARK-23803] Support Bucket Pruning
- [SPARK-24802] Optimization Rule Exclusion
- [SPARK-4502] Nested schema pruning for Parquet tables
- [SPARK-24296] Support replicating blocks larger than 2 GB
- [SPARK-24307] Support sending messages over 2GB from memory
- [SPARK-23243] Shuffle+Repartition on an RDD could lead to incorrect answers
- [SPARK-25181] Limited the size of BlockManager master and slave thread pools, lowering memory overhead when networking is slow
Connectors
- [SPARK-23972] Update Parquet from 1.8.2 to 1.10.0
- [SPARK-25419] Parquet predicate pushdown improvement
- [SPARK-23456] Native ORC reader is on by default
- [SPARK-22279] Use native ORC reader to read Hive serde tables by default
- [SPARK-21783] Turn on ORC filter push-down by default
- [SPARK-24959] Speed up count() for JSON and CSV
- [SPARK-24244] Parsing only required columns to the CSV parser
- [SPARK-23786] CSV schema validation - column names are not checked
- [SPARK-24423] Option query for specifying the query to read from JDBC
- [SPARK-22814] Support Date/Timestamp in JDBC partition column
- [SPARK-24771] Update Avro from 1.7.7 to 1.8
Kubernetes Scheduler Backend
- [SPARK-23984] PySpark bindings for K8S
- [SPARK-24433] R bindings for K8S
- [SPARK-23146] Support client mode for Kubernetes cluster backend
- [SPARK-23529] Support for mounting K8S volumes
PySpark
- [SPARK-24215] Implement eager evaluation for DataFrame APIs
- [SPARK-22274] User-defined aggregation functions with Pandas UDF
- [SPARK-22239] User-defined window functions with Pandas UDF
- [SPARK-24396] Add Structured Streaming ForeachWriter for Python
- [SPARK-23874] Upgrade Apache Arrow to 0.10.0
- [SPARK-25004] Add spark.executor.pyspark.memory limit
- [SPARK-23030] Use Arrow stream format for creating from and collecting Pandas DataFrames
- [SPARK-24624] Support mixture of Python UDF and Scalar Pandas UDF
Other notable changes
- [SPARK-24596] Non-cascading Cache Invalidation
- [SPARK-23880] Do not trigger any job for caching data
- [SPARK-23510] Support Hive 2.2 and Hive 2.3 metastore
- [SPARK-23711] Add fallback generator for UnsafeProjection
- [SPARK-24626] Parallelize location size calculation in Analyze Table command

Programming guides: Spark RDD Programming Guide and Spark SQL, DataFrames and Datasets Guide.

Structured Streaming

Major features
- [SPARK-24565] Exposed the output rows of each microbatch as a DataFrame using foreachBatch (Python, Scala, and Java)
- [SPARK-24396] Added Python API for foreach and ForeachWriter
- [SPARK-25005] Support “kafka.isolation.level” to read only committed records from Kafka topics that are written using a transactional producer.
Other notable changes
- [SPARK-24662] Support the LIMIT operator for streams in Append or Complete mode
- [SPARK-24763] Remove redundant key data from value in streaming aggregation
- [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] Support for choosing either the min or max watermark when there are multiple input streams in a query
- [SPARK-25399] Fixed a bug where reusing execution threads from continuous processing for microbatch streaming can result in a correctness issue
- [SPARK-18057] Upgraded Kafka client version from 0.10.0.1 to 2.0.0

Programming guide: Structured Streaming Programming Guide.

MLlib

Major features
- [SPARK-22666] Spark datasource for image format
Other notable changes
- [SPARK-22119] Add cosine distance measure to KMeans/BisectingKMeans/Clustering evaluator
- [SPARK-10697] Lift Calculation in Association Rule mining
- [SPARK-14682] Provide evaluateEachIteration method or equivalent for spark.ml GBTs
- [SPARK-7132] Add fit with validation set to spark.ml GBT
- [SPARK-15784] Add Power Iteration Clustering to spark.ml
- [SPARK-15064] Locale support in StopWordsRemover
- [SPARK-21741] Python API for DataFrame-based multivariate summarizer
- [SPARK-21898] Feature parity for KolmogorovSmirnovTest in MLlib
- [SPARK-10884] Support prediction on single instance for regression and classification related models
- [SPARK-23783] Add new generic export trait for ML pipelines
- [SPARK-11239] PMML export for ML linear regression

Programming guide: Machine Learning Library (MLlib) Guide.

SparkR

Major features
- [SPARK-25393] Adding new function from_csv()
- [SPARK-21291] add R partitionBy API in DataFrame
- [SPARK-25007] Add array_intersect/array_except/array_union/shuffle to SparkR
- [SPARK-25234] avoid integer o

Download Spark Img Editor