TARGET_RDBMS: MySQL-5.X-InnoDB ("X" equals current stable release)
BACKGROUND: Building my first database with true referential integrity constraints, in an effort to get feedback, after creating the "real" DDL, I've made an abstraction that I believe covers the "feel" of the database; this is only 3 tables of about 20, all with referential integrity constraints; only pattern I see that is missing is a composite key table, which does not have data to be dumped in right now anyway, so I'm just focus on the first iteration.
Sample Data / Unit Test: One thing I do not know is how to build out a sample data set that will offer 100% coverage of the referential integrity modeled -- AND build "Unit Test" around that sample data and this DDL:
Sample DLL:
(Note: Just to be clear, the LEGEND and naming standards are JUST for this example, which I've abstracted from the "real" database. The column names are robotic in nature, and meant to make the meaning and relationship of a given instance as clear as possible. If you have suggestions on the notation system used, please feel free to comment. I'm open to any suggestions. Thanks!)
CREATE DATABASE sampleDB;
use sampleDB;
# ###############
# LEGEND
# - sID = surrogate key
# - nID = natural key
# - cID = common/shared across tables, but NOT unique/natural-key
# - PK = Primary Key
# - FK = Foreign Key
# - data01 = Sample data (non-key,not-shared-across-tables)
# - data02 = Sample data NOT NULL (non-key,not-shared-across-tables)
#
# - uID = user defined unique/natural key (NOTE: not used)
# ###############
# Behavior
# - create_timestamp (NOT NULL, updated on record creation, NOT update)
# - update_timestamp (NOT NULL, updated on record creation AND updates)
CREATE TABLE `TABLE_01` (
`TABLE_01_sID_PK` MEDIUMINT NOT NULL AUTO_INCREMENT,
`TABLE_01_cID` int(8) NOT NULL,
`TABLE_01_data01` varchar(128) default NULL,
`TABLE_01_data02` varchar(128) default NULL,
`create_timestamp` DATETIME DEFAULT NULL,
`update_timestamp` TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
PRIMARY KEY (`TABLE_01_sID_PK`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
CREATE TABLE `TABLE_02` (
`TABLE_02_sID_PK` MEDIUMINT NOT NULL AUTO_INCREMENT,
`TABLE_02_nID_FK__TABLE_01_sID_PK` int(8) NOT NULL,
`TABLE_02_cID` int(8) NOT NULL,
`TABLE_02_data01` varchar(128) default NULL,
`TABLE_02_data02` varchar(128) NOT NULL,
`create_timestamp` DATETIME DEFAULT NULL,
`update_timestamp` TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
PRIMARY KEY (`TABLE_02_sID_PK`),
FOREIGN KEY (TABLE_02_nID_FK__TABLE_01_sID_PK) REFERENCES TABLE_01(TABLE_01_sID_PK),
INDEX `TABLE_02_nID_FK__TABLE_01_sID_PK` (`TABLE_02_nID_FK__TABLE_01_sID_PK`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
CREATE TABLE `TABLE_03` (
`TABLE_03_sID_PK` MEDIUMINT NOT NULL AUTO_INCREMENT,
`TABLE_03_nID_FK__TABLE_01_sID_PK` int(8) NOT NULL,
`TABLE_03_nID_FK__TABLE_02_sID_PK` int(8) NOT NULL,
`TABLE_03_cID` int(8) NOT NULL,
`TABLE_03_data01` varchar(128) default NULL,
`TABLE_03_data02` varchar(128) NOT NULL,
`create_timestamp` DATETIME DEFAULT NULL,
`update_timestamp` TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
PRIMARY KEY (`TABLE_03_sID_PK`),
FOREIGN KEY (TABLE_03_nID_FK__TABLE_01_sID_PK) REFERENCES TABLE_01(TABLE_01_sID_PK),
FOREIGN KEY (TABLE_03_nID_FK__TABLE_02_sID_PK) REFERENCES TABLE_02(TABLE_02_sID_PK),
INDEX `TABLE_03_nID_FK__TABLE_01_sID_PK` (`TABLE_03_nID_FK__TABLE_01_sID_PK`),
INDEX `TABLE_03_nID_FK__TABLE_02_sID_PK` (`TABLE_03_nID_FK__TABLE_02_sID_PK`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
SHOW TABLES;
# DROP DATABASE `sampleDB`;
# #######################
# View table definition
# DESC inserttablename;
# #######################
# View table create statement
# SHOW CREATE TABLE example;
Questions:
Any and all feedback on missing, wrong, or "better" ways to do this database build are welcome. If you have questions, just comment -- and I'll respond ASAP. Again, thanks~!
UPDATE (1):
Just added "MEDIUMINT NOT NULL AUTO_INCREMENT" to the PKs -- not sure how I left that off.
First of all, I want to applaud you for defining a standard. There is no end to how much it will come to help you in the future.
Having said that, a couple of very subjective opinions from my part:
I don't like to embed type information in names, such as "TABLE_PERSON" or "PERSON_T" because it becomes confusing the second you replace a table with a view instead. At this point you could of course search and replace "PERSON_T" with "PERSON_VW" instead, but it kind of misses the point :)
The same goes for columns (although i can't see this in your example). Think of the "n_is_dead" column that gets changed from numeric to varchar.
Can a row exist in a table without being created (create_timestamp)? Declare columns as NOT NULL if they really can't be null. In fact, I start of having NOT NULL on most of my columns because it makes me think harder about the nature of the data.
I'm a fan of naming the primary key column something other than ID. For example
company(company_id, etc)
person(person_id, company_id, firstname etc)
I've heard some people have problems with O/R mappers that want you to have the primary key named "ID" at all times, but I don't know if this is still true of if this has changed recently.
It's not clear to me if you intented to embed (s,n,c) in the column names to indicate whether they are surrogate, natural or common key. But I also don't think this is a good idea. I feel that would "reveal" some implementation detail that doesn't fit naturally in the logical model.
It looks like you are exposing/embedding the foreign key relationship in the column names. I have never thought of this, but I think you will deeply regret this one. If not only because it makes the column names unbearably uggly :)
When choosing a name for an index. The only time I regret naming an index something is when I look at an execution plan and see "index_01" being used. I always wish I had put the column name in the index to make it visible in the xplan. I don't know the limit for an index name, but I always run into the limit on Oracle. So, try to come up with some rule for how to abbreviate the table name. The column name is the important thing here.
Regarding mixed case. I always (no exceptions) go with either ALL_UPPER_CASE or all_lower_case. The reason is that in the past I've been burned when migrating queries between databases when they treat case differently. Lately, I use all_lower_case because the typical font of our editors makes it easier to spot spelling errors in lower case than in upper case. And when I fail at things, it doesn't seem like the editor is SHOUTING AT ME ;)
Related
I am currently facing an issue with designing a database table and updating/inserting values into it.
The table is used to collect and aggregate statistics that are identified by:
the source
the user
the statistic
an optional material (e.g. item type)
an optional entity (e.g. animal)
My main issue is, that my proposed primary key is too large because of VARCHARs that are used to identify a statistic.
My current table is created like this:
CREATE TABLE `Statistics` (
`server_id` varchar(255) NOT NULL,
`player_id` binary(16) NOT NULL,
`statistic` varchar(255) NOT NULL,
`material` varchar(255) DEFAULT NULL,
`entity` varchar(255) DEFAULT NULL,
`value` bigint(20) NOT NULL)
In particular, the server_id is configurable, the player_id is a UUID, statistic is the representation of an enumeration that may change, material and entity likewise. The value is then aggregated using SUM() to calculate the overall statistic.
So far it works but I have to use DELETE AND INSERT statements whenever I want to update a value, because I have no primary key and I can't figure out how to create such a primary key in the constraints of MySQL.
My main question is: How can I efficiently update values in this table and insert them when they are not currently present without resorting to deleting all the rows and inserting new ones?
The main issue seems to be the restriction MySQL puts on the primary key. I don't think adding an id column would solve this.
Simply add an auto-incremented id:
CREATE TABLE `Statistics` (
statistis_id int auto_increment primary key,
`server_id` varchar(255) NOT NULL,
`player_id` binary(16) NOT NULL,
`statistic` varchar(255) NOT NULL,
`material` varchar(255) DEFAULT NULL,
`entity` varchar(255) DEFAULT NULL,
`value` bigint(20) NOT NULL
);
Voila! A primary key. But you probably want an index. One that comes to mind:
create index idx_statistics_server_player_statistic on statistics(server_id, player_id, statistic)`
Depending on what your code looks like, you might want additional or different keys in the index, or more than one index.
Follow the below hope it will solve your problem :-
- First use a variable let suppose "detailed" as money with your table.
- in your project when you use insert statement then before using statement get the maximum of detailed (SELECT MAX(detailed)+1 as maxid FROM TABLE_NAME( and use this as use number which will help you to FETCH,DELETE the record.
-you can also update with this also BUT during update MAXIMUM of detailed is not required.
Hope you understand this and it will help you .
I have dug a bit more through the internet and optimized my code a lot.
I asked this question because of bad performance, which I assumed was because of the DELETE and INSERT statements following each other.
I was thinking that I could try to reduce the load by doing INSERT IGNORE statements followed by UPDATE statements or INSERT .. ON DUPLICATE KEY UPDATE statements. But they require keys to be useful which I haven't had access to, because of constraints in MySQL.
I have fixed the performance issues though:
By reducing the amount of statements generated asynchronously (I know JDBC is blocking but it worked, it just blocked thousand of threads) and disabling auto-commit, I was able to improve the performance by 600 times (from 60 seconds down to 0.1 seconds).
Next steps are to improve the connection string and gaining even more performance.
I want to add a column to my users table and generate slug for all of them. The problem is I have over 1 million users in my DB.
I have seen various blogs explaining different methods but I do not want to take risk by doing it in my production DB.
Methods that I found:
The below method suggests to add the code to generate slug in migration file itself.
class AddStatusToUser < ActiveRecord::Migration
class User < ActiveRecord::Base
end
def up
add_column :users, :status, :string
User.find_each do |user|
user.status = 'active'
user.save!
end
end
def down
remove_column :users, :status
end
end
I have written this method which is run by a rake task:
The problem with the below one is that it has been running 4 days in which only 400 000 slugs have been generated so far. I wanted to do it quickly, but do not know how.
find_in_batches:
Yields each batch of records that was found by the find options as an
array. The size of each batch is set by the :batch_size option; the
default is 1000.
You can control the starting point for the batch processing by
supplying the :start option. This is especially useful if you want
multiple workers dealing with the same processing queue. You can make
worker 1 handle all the records between id 0 and 10,000 and worker 2
handle from 10,000 and beyond (by setting the :start option on that
worker).
It’s not possible to set the order. That is automatically set to
ascending on the primary key (“id ASC”) to make the batch ordering
work. This also mean that this method only works with integer-based
primary keys. You can’t set the limit either, that’s used to control
the batch sizes.
In order to avoid DB performance issues I have given a sleep time of 2 seconds after every slug generation for 1000 users. Should I remove the sleep method? Should I just run User.find_each(&:save) or method 1?
task :add_slug_to_all_users => :environment do
i=0
batchSize = 1000
puts "started at :#{Time.now}"
# find_in_batches method provides the users in batches of 1000
# so that the update is not triggered for all the rows at once which may lock the table completely.
User.where("slug is null and email is not null").find_in_batches(batch_size: batchSize) do |users|
sleep(2)
users.each {|u| u.save!; i+=1;}
puts "updated #{i} records at: #{Time.now}"
end
puts "Completed the Task at: #{Time.now}\n"
end
Update 1: I am using friendly_id gem to generate slugs.
Update 2: I have run SHOW CREATE TABLE users and I got this:
CREATE TABLE `users` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`first_name` varchar(255) COLLATE utf8_unicode_ci DEFAULT NULL,
`last_name` varchar(255) COLLATE utf8_unicode_ci DEFAULT NULL,
`p_views` int(11) DEFAULT '0',
`p_desc` text COLLATE utf8_unicode_ci,
`p_title` text COLLATE utf8_unicode_ci,
`created_at` datetime DEFAULT NULL,
`updated_at` datetime DEFAULT NULL,
`t_zone` varchar(255) COLLATE utf8_unicode_ci DEFAULT 'UTC',
`college` varchar(500) COLLATE utf8_unicode_ci DEFAULT NULL,
`degree` text COLLATE utf8_unicode_ci,
`p_no` varchar(15) COLLATE utf8_unicode_ci DEFAULT NULL,
`slug` varchar(255) COLLATE utf8_unicode_ci DEFAULT NULL,
PRIMARY KEY (`id`),
UNIQUE KEY `unique_phone_number` (`p_no`),
UNIQUE KEY `index_users_on_phone_no` (`p_no`),
UNIQUE KEY `index_users_on_slug` (`slug`),
KEY `use_index_on_college` (`college`(255))
) ENGINE=InnoDB AUTO_INCREMENT=2194 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci |
Please note that I have removed most of the fields from the above result. The column slug stores the combination of first_name and last_name in a url friendly manner.
For e.g. if a user's name is:
id first_name last_name
1 Arun Kumar
2 Arun Kumar
The slug generated would look like this:
id slug
1 arun-kumar
2 arun-kumar1
In a situation like this, all-purpose 3rd party software can only get in the way. You would be better off going down to the SQL to do the work.
If the "slug" is a simple sequence number, then adding an AUTO_INCREMENT would be the obvious solution, and a permanent solution. That is, all future additions would have the slug automatically generated. That could be done with one statement:
ALTER TABLE t
ADD COLUMN slug INT UNSIGNED AUTO_INCREMENT,
INDEX(slug);
It would possibly be better for slug to be the PRIMARY KEY (Please provide SHOW CREATE TABLE.) But that would probably require a serious lock on the table; so a plain index is better. Test it. It may be "fast enough".
The next thought is pt-online-schema-change (see Percona.com), which is a special tool for effectively doing ALTERs with nearly zero impact. It involves adding a TRIGGER to capture writes, and chunking of the copying. The slight impact comes with the "last little bit" needs to be copied. The final RENAME TABLE real TO old, new TO real; is atomic and essentially instantaneous. It even dynamically tunes the "sleep". It is an excellent tool with many years of experience put into it.
But, ptosc may not work for adding something as critical as the PRIMARY KEY, hence my suggestion (above) of a plain INDEX.
Setting the values (via UPDATE), one chunk at a time, is the right way to go. I have written on chunking tips; that was aimed at DELETE, but can be adapted to UPDATE.
Without knowing what is "under the covers" in find_in_batches(), I cannot say that it is good or bad. I do know that OFFSET is almost always bad; "remembering where you left off" is usually much better. But it is hard to do that if you don't already have a UNIQUE or PRIMARY key. PRIMARY is better because of its clustering. (Please provide SHOW CREATE TABLE, so I don't have to make guesses.)
If your sample code starts over at the beginning of the table each time, then it is as bad as using OFFSET -- each iteration will be slower than the previous because it is skipping over more and more rows.
After adding a column, be sure to check all references to the table -- SELECT * will now have one more column (one reason for not using *). UPDATEs and INSERTs may work with the missing column, but you need to check.
Update
There were two steps -- add the slug column, and populate it. You have done the first step.
To do the second step, I recommend stepping through the table 100 rows at a time, using the AUTO_INCREMENT PRIMARY KEY. 100 is low enough to be not-too-invasive. The AI PK will cover the entire table, and is efficient so that you don't need a slow OFFSET or search for un-slugged set. I discuss efficient chunking here. It is written with DELETE in mind, but the techniques apply to UPDATE.
I'm trying to implement a way to track changes to a table named user and another named report_to Below are their definitions:
CREATE TABLE `user`
(
`agent_eid` int(11) NOT NULL,
`agent_id` int(11) DEFAULT NULL,
`agent_pipkin_id` int(11) DEFAULT NULL,
`first_name` varchar(45) NOT NULL,
`last_name` varchar(45) NOT NULL,
`team_id` int(11) NOT NULL,
`hire_date` date NOT NULL,
`active` bit(1) NOT NULL,
`agent_id_req` bit(1) NOT NULL,
`agent_eid_req` bit(1) NOT NULL,
`agent_pipkin_req` bit(1) NOT NULL,
PRIMARY KEY (`agent_eid`),
UNIQUE KEY `agent_eid_UNIQUE` (`agent_eid`),
UNIQUE KEY `agent_id_UNIQUE` (`agent_id`),
UNIQUE KEY `agent_pipkin_id_UNIQUE` (`agent_pipkin_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8
CREATE TABLE `report_to`
(
`agent_eid` int(11) NOT NULL,
`report_to_eid` int(11) NOT NULL,
PRIMARY KEY (`agent_eid`),
UNIQUE KEY `agent_eid_UNIQUE` (`agent_eid`),
KEY `report_to_report_fk_idx` (`report_to_eid`),
CONSTRAINT `report_to_agent_fk` FOREIGN KEY (`agent_eid`) REFERENCES `user` (`agent_eid`) ON DELETE NO ACTION ON UPDATE NO ACTION,
CONSTRAINT `report_to_report_fk` FOREIGN KEY (`report_to_eid`) REFERENCES `user` (`agent_eid`) ON DELETE NO ACTION ON UPDATE NO ACTION
) ENGINE=InnoDB DEFAULT CHARSET=utf8
What can change that needs to be tracked is user.team_id, user.active and report_to.report_to_eid. What i currently have implemented is a table that is populated via an update trigger on user that tracks team changes. That table is defined as:
CREATE TABLE `user_team_changes`
(
`agent_id` int(11) NOT NULL,
`date_changed` date NOT NULL,
`old_team_id` int(11) NOT NULL,
`begin_date` date NOT NULL,
PRIMARY KEY (`agent_id`,`date_changed`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8
This works fine for just tracking team changes. I'm able to use joins and a union to populate a history view that tracks that change over time for the individual users. The issue of complexity rises when I try to implement tracking for the other two change types.
I have thought about creating additional tables similar to the one tracking changes for teams, but I worry about performance hits due to the joins that will be required.
Another way I have considered is creating a table similar to a view that I have that details the current user state (it joins all necessary user data together from 4 tables), then insert a record on update with a valid until date field added. My concern with that is the amount of space this could take.
We will be using the user change history quite a bit as we will be running YTD, MTD, PMTD and time interval reports with it on an almost daily basis.
Out of the two options I am considering, which would be the best for my given situation?
The options you've presented:
using triggers to populate transaction-log tables.
including a new table with an effective-date columns in the schema and tracking change by inserting new rows.
Either one of these will work. You can add logging triggers to other tables without causing any trouble.
What distinguishes these two choices? The first one is straightforward, once you get your triggers debugged.
The second choice seems to me that it will create denormalized redundant data. That is never good. I would opt not to do that. It is possible with judicious combinations of views and effective-date columns to create history tables that are viewable as the present state of the system. To learn about this look at Prof. RT Snodgrass's excellent book on Developing Time Oriented applications. http://www.cs.arizona.edu/~rts/publications.html If you have time to do an excellent engineering (over-engineering?) job on this project you might consider this approach.
The data volume you've mentioned will not cause intractable performance problems on any modern server hardware platform. If you do get slowdowns on JOIN operations, it's almost certain that the addition of appropriate indexes will completely fix them, as long as you declare all your DATE, DATETIME, and TIMESTAMP fields NOT NULL. (NULL values can mess up indexing and searching).
Hope this helps.
I am currently working on a project, which involves altering data stored in a MYSQL database. Since the table that I am working on does not have a key, I add a key with the following command:
ALTER TABLE deCoupledData ADD COLUMN MY_KEY INT NOT NULL AUTO_INCREMENT KEY
Due to the fact that I want to group my records according to selected fields, I try to create an index for the table deCoupledData that consists of MY_KEY, along with the selected fields. For example, If I want to work with the fields STATED_F and NOT_STATED_F, I type:
ALTER TABLE deCoupledData ADD INDEX (MY_KEY, STATED_F, NOT_STATED_F)
The real issue is that the fields that I usually work with are more than 16, so MYSQL does not allow super-keys longer than 16 fields.
In conclusion, Is there another way to do this? Can I make (somehow) MYSQL to order the records according to the desired super-key (something like clustering)? I really need to make my script faster and the main overhead is that each group may contain records which are not stored on the same page of the disk, and I assume that my pc starts random I/Os in order to retrieve records.
Thank you for your time.
Nick Katsipoulakis
CREATE TABLE deCoupledData (
AA double NOT NULL DEFAULT '0',
STATED_F double DEFAULT NULL,
NOT_STATED_F double DEFAULT NULL,
MIN_VALUES varchar(128) NOT NULL DEFAULT '-1,-1',
MY_KEY int(11) NOT NULL AUTO_INCREMENT,
PRIMARY KEY (MY_KEY),
KEY AA (AA) )
ENGINE=InnoDB AUTO_INCREMENT=74358 DEFAULT CHARSET=latin1
Okay, first of all, when you add an index over multiple columns and you don't really use the first column, the index is useless.
Example: You have a query like
SELECT *
FROM deCoupledData
WHERE
stated_f = 5
AND not_stated_f = 10
and an index over (MY_KEY, STATED_F, NOT_STATED_F).
The index can only be used, if you have another AND my_key = 1 or something in the WHERE clause.
Imagine you want to look up every person in a telephone book with first name 'John'. Then the knowledge that the book is sorted by last name is useless, you still have to look up every single name.
Also, the primary key does not have to be a surrogate / artificial one. It's nearly always better to have a primary key which is made up of columns which identify each row uniquely anyway.
Also it's not always good to have many indexes. Not only do indexes slow down INSERTs and UPDATEs, sometimes they just cause an extra lookup, since first a look at the index is taken and a second look to find the actual data.
That's just a few tips. Maybe Jordan's hint is not a bad idea, "You should maybe post a new question that has your actual SQL query, table layout, and performance questions".
UPDATE:
Yes, that is possible. According to manual
If you define a PRIMARY KEY on your table, InnoDB uses it as the clustered index.
which means that the data is practically sorted on disk, yes.
Be aware that it's also possible to define a primary key over multiple columns!
Like
CREATE TABLE deCoupledData (
AA double NOT NULL DEFAULT '0',
STATED_F double DEFAULT NULL,
NOT_STATED_F double DEFAULT NULL,
MIN_VALUES varchar(128) NOT NULL DEFAULT '-1,-1',
MY_KEY int(11) NOT NULL AUTO_INCREMENT,
PRIMARY KEY (NOT_STATED_F, STATED_F, AA),
KEY AA (AA) )
ENGINE=InnoDB AUTO_INCREMENT=74358 DEFAULT CHARSET=latin1
as long as the combination of the columns is unique.
I am about to design a database for a logging system.
Many of the String columns will have a limited amount of values, but not known in advance:
Like the name of the modules sending the messages, or the source hostnames.
I would like to store them as MySQL Enums to save space.
So the idea would be that the Enums grow as they encounter new values.
I would start with a column like :
host ENUM('localhost')
Then, in Java, I would load on startup the enum values defined for the hostnames at a time (how do I do that with MySQL/JDBC ??), and I would alter the Enum whenever I encounter a new host.
Do you think it is feasible / a good idea ?
Have you ever done something like that ?
Thanks in advance for your advice.
Raphael
This is a not good idea. ENUM designed not for that.
You can just create separate table (host_id, host_name) and use refference in main table. Example:
CREATE TABLE `host` (
`host_id` INT(10) NOT NULL AUTO_INCREMENT,
`host_name` VARCHAR(50) NULL DEFAULT NULL,
PRIMARY KEY (`host_id`)
)
CREATE TABLE `log` (
`log_id` INT(10) NOT NULL AUTO_INCREMENT,
`host_id` INT(10) NULL DEFAULT NULL,
...
PRIMARY KEY (`log_id`),
INDEX `FK__host` (`host_id`),
CONSTRAINT `FK__host` FOREIGN KEY (`host_id`) REFERENCES `host` (`host_id`) ON UPDATE CASCADE ON DELETE CASCADE
)
UPD:
I think the best way to storing host is varchar/text field. It is easiest and fastest way. I think you need not worry about the space.
Nonetheless.
Using the second table for hosts will reduce the size, but will complicate writing logs. Using ENUM complicate writing and significantly reduce the performance.