Home
files- img
- spark-ml-source-analysis
- yml
- 数据分析
Amundsen.md- Apache-Beam.md
- Apache-Ignite.md
- Apache-Kudu.md
- Apache-Kylin.md
- Apache-kyuubi.md
- Apache-Zeppelin.md
- awesome.md
- BI-可视化.md
- CDC.md
- CDH.md
- DB.md
- ETL.md
- Flink-1.md
- Flink-Dev.md
- Flink-on-k8s.md
- Flink-SQL.md
- Flink-Stateful-Functions.md
- Flink.md
- go-hadoop.md
- Google-Dataflow-Model.md
- Hadoop-HDFS.md
- hadoop-spark-install.md
- Hadoop-Spark.md
- Hadoop.md
- Hbase.md
- openLooKeng.md
- PyFlink.md
- pyspark.md
- README.md
- spark-binlog.md
- Spark-Info.md
- spark-info2.md
- Spark-memory.md
- spark-ml.md
- Spark-on-Kubernetes.md
- spark-performance.md
- spark-posts.md
- spark-ppt素材.md
- spark-rdd.md
- spark-Structured-Streaming.md
- Spark-submit.md
- Spark-TFRecord.md
- spark-v3.0.md
- Spark-VS-Flink.md
- Spark.md
- spark2.md
- SparkSQL.md
- Structured-Streaming-VS-Flink.md
- tools.md
- 什么是Hadoop为什么是Spark.md
- 分析方法.md
- 推荐引擎.md
- 搜索指数.md
- 模型选择和训练-验证-测试集.md
- 用户画像.md
https://blog.csdn.net/young_0609/article/details/102986027
http://spark.apache.org/
https://www.iteblog.com/archives/category/spark/
Apache Spark 3.0 增加了很多令人兴奋的新特性，包括动态分区修剪（Dynamic Partition Pruning）、自适应查询执行（Adaptive Query Execution）、加速器感知调度（Accelerator-aware Scheduling）、支持 Catalog 的数据源API（Data Source API with Catalog Supports）、SparkR 中的向量化（Vectorization in SparkR）、支持 Hadoop 3/JDK 11/Scala 2.12 等等。Spark 3.0.0-preview 中主要特性和变化的完整列表请参阅这里。下面我将带领大家解析一些比较重要的新特性。