bulkinsert

SOLR - Best approach to import 20 million documents from csv file

▼魔方 西西 提交于 2019-11-30 12:46:06
问题 My current task on hand is to figure out the best approach to load millions of documents in solr. The data file is an export from DB in csv format. Currently, I am thinking about splitting the file into smaller files and having a script while post this smaller ones using curl. I have noticed that if u post high amount of data, most of the time the request times out. I am looking into Data importer and it seems like a good option Any others ideas highly appreciated Thanks 回答1: Unless a

SQLBulkCopy or Bulk Insert

≡放荡痞女 提交于 2019-11-30 11:42:29
I have about 6500 files for a sum of about 17 GB of data, and this is the first time that I've had to move what I would call a large amount of data. The data is on a network drive, but the individual files are relatively small (max 7 MB). I'm writing a program in C#, and I was wondering if I would notice a significant difference in performance if I used BULK INSERT instead of SQLBulkCopy. The table on the server also has an extra column, so if I use BULK INSERT I'll have to use a format file and then run an UPDATE for each row. I'm new to forums, so if there was a better way to ask this

Mysql Bulk Update

霸气de小男生 提交于 2019-11-30 09:26:32
I have to execute ~6k update queries on a table through sql (No Hibernate/JDBC). Query is something like update A set some_id='value1' where id='value2' It takes too long to execute all these queries. Is there a way to improve the performance? Create a temp table (containing just the value1 and value2 values) and populate it in bulk (ie, you can potentially do this with a single insert statement). Then do an update using a join between your existing table and the temp table. Something like INSERT INTO SomeTempTable(id, some_id) VALUES (1,2), (3,4), (5,6), ....... UPDATE A INNER JOIN

How does BULK INSERT work internally?

时间秒杀一切 提交于 2019-11-30 09:21:37
Could someone please explain how does BULK INSERT internally work and why is it much faster than the normal INSERT operations ? Regards, Shishir. BULK INSERT runs in-process with the database engine of SQL Server and thus avoids passing data through the network layer of the Client API - this makes it faster than BCP and DTS / SSIS. Also, with BULK INSERT, you can specify the ORDER BY of the data, and if this is the same as the PK of the table, then the locking occurs at a PAGE level. Writes to the transaction logs happen at a page level rather than a row level as well. In the case of regular

Doctrine 2: weird behavior while batch processing inserts of entities that reference other entities

孤街浪徒 提交于 2019-11-30 08:38:51
问题 I am trying out the batch processing method described here: http://docs.doctrine-project.org/projects/doctrine-orm/en/latest/reference/batch-processing.html my code looks like this $limit = 10000; $batchSize = 20; $role = $this->em->getRepository('userRole')->find(1); for($i = 0; $i <= $limit; $i++) { $user = new \Entity\User; $user->setName('name'.$i); $user->setEmail('email'.$i.'@email.blah'); $user->setPassword('pwd'.$i); $user->setRole($role); $this->em->persist($user); if (($i %

Bulk insert in MongoDB using mongoose

北战南征 提交于 2019-11-30 08:14:49
问题 I currently have a collection in Mongodb say "Collection1". I have the following array of objects that need to be into inserted into MongoDB. I am using Mongoose API. For now, I am iterating through the array and inserting each of them into mongo. This is ok for now, but will be a problem when the data is too big. I need a way of inserting the data in bulk into MongoDB without repetition. I am not sure how to do this. I could not find a bulk option in Mongoose. My code below myData = [Obj1

Bulk insert of hundreds of millions of records

萝らか妹 提交于 2019-11-30 07:38:32
What is the fastest way to insert 237 million records into a table that has rules (for distributing data across child tables)? I have tried or considered: Insert statements. Transactional inserts ( BEGIN and COMMIT ). The COPY FROM command. http://pgbulkload.projects.postgresql.org/ Inserts are too slow (four days) and COPY FROM ignores rules (and has other issues). Example data: station_id,taken,amount,category_id,flag 1,'1984-07-1',0,4, 1,'1984-07-2',0,4, 1,'1984-07-3',0,4, 1,'1984-07-4',0,4,T Table structure (with one rule included): CREATE TABLE climate.measurement ( id bigserial NOT NULL,

Sqlalchemy bulk update in MySQL works very slow

安稳与你 提交于 2019-11-30 05:39:08
问题 I'm using SQLAlchemy 1.0.0 , and want to make some UPDATE ONLY (update if match primary key else do nothing) queries in batch. I've made some experiment and found that bulk update looks much slower than bulk insert or bulk upsert . Could you please help me to point out why it works so slow or is there any alternative way/idea to make the BULK UPDATE (not BULK UPSERT) with SQLAlchemy ? Below is the table in MYSQL: CREATE TABLE `test` ( `id` int(11) unsigned NOT NULL, `value` int(11) DEFAULT

Why Bulk Import is faster than bunch of INSERTs?

有些话、适合烂在心里 提交于 2019-11-30 04:14:05
问题 I'm writing my graduate work about methods of importing data from file to SQL Server table. I have created my own programm and now I'm comparing it with some standart methods as bcp, BULK INSERT, INSERT ... SELECT * FROM OPENROWSET(BULK...). My program read in lines from file, parse them and import them one by one using ordinary INSERTs. I have generated file with 1 million lines each with 4 columns for tests. And now I have situation that my program works 160 seconds while standart methods 5

Improve insert performance massively

南笙酒味 提交于 2019-11-30 03:23:57
问题 In my application I need to massively improve insert performance. Example: A file with about 21K records takes over 100 min to insert. There are reasons it can takes some time, like 20 min or so but over 100 min is just too long. Data is inserted into 3 tables (many-to-many). Id's are generated from a sequence but I have already googled and set hibernate.id.new_generator_mappings = true and allocationSize + sequence increment to 1000. Also the amount of data is not anything extraordinary at