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Hierarchical Data Format (HDF) is a set of file formats (HDF4, HDF5) designed to store and organize large amounts of data.Originally developed at the U.S. National Center for Supercomputing Applications, it is supported by The HDF Group, a non-profit corporation whose mission is to ensure continued development of HDF5 technologies and the continued accessibility of data stored in HDF.
This can have a significant impact on job-completion times as demonstrated with data-intensive jobs. [43] HDFS was designed for mostly immutable files and may not be suitable for systems requiring concurrent write operations. [41] HDFS can be mounted directly with a Filesystem in Userspace (FUSE) virtual file system on Linux and some other Unix ...
Tables in HBase can serve as the input and output for MapReduce jobs run in Hadoop, and may be accessed through the Java API but also through REST, Avro or Thrift gateway APIs. HBase is a wide-column store and has been widely adopted because of its lineage with Hadoop and HDFS. HBase runs on top of HDFS and is well-suited for fast read and ...
Calcite: dynamic data management framework; Camel: declarative routing and mediation rules engine which implements the Enterprise Integration Patterns using a Java-based domain specific language; CarbonData: an indexed columnar data format for fast analytics on big data platform, e.g., Apache Hadoop, Apache Spark, etc
Apache Hive is a data warehouse software project. It is built on top of Apache Hadoop for providing data query and analysis. [3] [4] Hive gives an SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop.
Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. [1] Trino can query data lakes that contain open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like HDFS, AWS S3, Google Cloud Storage, or Azure Blob Storage [4] using the Hive [2] and Iceberg [3 ...
Presto (including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata, [1] and allows use of multiple data sources within a query.
The way data is distributed across HDFS makes it expensive to join data. In a distributed relational database we can co-locate records with the same primary and foreign keys on the same node in a cluster. This makes it relatively cheap to join very large tables. No data needs to travel across the network to perform the join.
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