partitioning

问题 I am going to create a SQL tables in Azure SQL database, and I want to create a partition of table, but I don't know how to do that, can any one show me some demo example or query to perform this. I am using SQL management studio to connect my Azure db. 回答1: We take advantage of partitioning SQL Azure tables. We use it so we can rapidly truncate the oldest partitions of data. We have a great blog post that walks through step by step how to do it: https://stackify.com/how-to-partition-tables

问题 Let's assume, I have a REST API serving an entity. My aim is to find a way to effectively split the attributes of the entity used by Update calls (PATCH/PUT) in such a way that the resulting combination of columns are disjoint (or nearly). If they are disjoint (best case), then it is easier, to split that given API to many sub APIs, which do not affect each other and thereby accessing disjoint columns in the table entity.This further allows to perhaps split that table to multiple sub tables.

问题 This is a quote from jaceklaskowski.gitbooks.io. Some operations, e.g. map, flatMap, filter, don’t preserve partitioning. map, flatMap, filter operations apply a function to every partition. I don't understand why filter does not preserve partitioning. It's just getting a subset of each partition which satisfy a condition so I think partitions can be preserved. Why isn't it like that? 回答1: You are of course right. The quote is just incorrect. filter does preserve partitioning (for the reason

问题 I have a very large file (20GB+ compressed) called input.json containing a stream of JSON objects as follows: { "timestamp": "12345", "name": "Some name", "type": "typea" } { "timestamp": "12345", "name": "Some name", "type": "typea" } { "timestamp": "12345", "name": "Some name", "type": "typeb" } I want to split this file into files dependent on their type property: typea.json , typeb.json etc., each containing their own stream of json objects that only have the matching type property. I've

问题 Does anybody know this algorithm a little bit, because I'm considering using it, but I'm not sure whether it really meets all my requirements. So bascially, what I want to do is splitting up a graph in several subgraphs. However the nodes of each subgraph should be connected, that is it should not be the case that for example if I want to reach node x I have to go through another subgraph. And that is exactly my concern. Is it possible, that when I split up a graph with the Kernighan-Lin

问题 I am running a Airflow DAG which moves data from GCS to BQ using operator GoogleCloudStorageToBigQueryOperator i am on Airflow version 1.10.2. This task moves data from MySql to BQ(Table partitioned), all this time we were partitioned by Ingestion-time and the incremental load for past three days were working fine when the data was loaded using Airflow DAG. Now we changed the partitioned type to be Date or timestamp on a DATE column from the table, after which we have started getting this

问题 I have data that looks as such: +-----+--------+--------+--------+ | ID | score1 | score2 | score3 | +-----+--------+--------+--------+ | 123 | 14 | 561 | 580 | | 123 | 626 | 771 | 843 | | 123 | 844 | 147 | 904 | | 456 | 922 | 677 | 301 | | 456 | 665 | 578 | 678 | | 456 | 416 | 631 | 320 | +-----+--------+--------+--------+ What I'm trying to do is create another column that provides which score is the highest amongst the three. Remember, I'm not looking for what the value is, I'm looking for

问题 I have a Hive DB - I created a table, compatible to Parquet file type. CREATE EXTERNAL TABLE `default.table`( `date` date, `udid` string, `message_token` string) PARTITIONED BY ( `dt` date) ROW FORMAT SERDE 'org.apache.hadoop.hive.ql.io.parquet.serde.ParquetHiveSerDe' STORED AS INPUTFORMAT 'org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat' OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.parquet.MapredParquetOutputFormat' LOCATION 's3://Bucket/Folder') I added partitions to this table,

问题 I'm having difficulty understanding the difference between the partition keys & the partition key ranges in Cosmos DB. I understand generally that a partition key in cosmos db is a JSON property/path within each document that is used to evenly distribute data among multiple partitions to avoid any uneven "hot partitions" -- and partition key decides the physical placement of documents. But its not clear to me how what the partition key range is...is this just a range of literal partition keys

问题 I have to implement a partitioning for the column data ( Column Name : ID ) for a very large database table ( DB2 ). Table has more than a billion rows and keeps growing. Partitioning has to be implemented like illustrated here i.e. I have to calculate minId & maxId for a specified range. ID column values are unique but not sequential so simple approach as illustrated in above link will not work - i.e. starting from an ID then keep adding range. WITH ROWNUMTAB AS ( SELECT ROWNUM, ID FROM (