I'm trying to create one table from another using
CREATE TABLE IF NOT EXISTS new_data ENGINE = ReplicatedReplacingMergeTree(/clickhouse/fedor/tables/{shard}/subfolder/new_data', '{replica}')
ORDER BY created_at
SETTINGS index_granularity = 8192, allow_nullable_key=TRUE
AS
SELECT *
FROM table
WHERE column IS NOT NULL
When I use
ENGINE = ReplicatedReplacingMergeTree('/clickhouse/fedor/tables/{shard}/subfolder/new_data', '{replica}'),
i've got around 7-9% of expected number of rows i've got from query SELECT...FROM...WHERE
When I use
ENGINE = ReplicatedMergeTree('/clickhouse/fedor/tables/{shard}/subfolder/new_data', '{replica}')
i've got 3 times more than expected (I assume every row occur exactly 3 times)
I would like to have exact number of rows without losses and without duplication
ReplicatedReplacingMergeTree with ORDER BY created_at
will replace many rows with the same created_at value to one rows
How did you delete exists table data before create
ReplicatedMergeTree('/clickhouse/fedor/tables/{shard}/subfolder/new_data'...)?
Did you use DROP TABLE new_data SYNC?
Which engine do you have for table?
Related
So my use case is i have to find the location of the primary key column so that i can write query like select * from my_table where ID <='00000536-37ee-471c-a8e0-3d233b8102f5'
So my table has a primary key which is varchar type and values of the column is GUID generated by an application.
Here is an example of primary key
000000bd-104e-4fd6-a791-c5422f29e1b5
0000016e-7e68-4453-b360-7ffd1627dc22
00000196-2dba-4532-8cba-1e853c466697
0000025a-cfae-41b4-b8e7-ef854d49e54a
00000260-8bdb-4b30-acdb-5a67efd4dbfe
00000366-552d-48a0-b8a1-20190ccd087c
000003f2-d6d8-4a51-96cc-407063bc568b
000003ff-3d16-4e88-9cf3-bcdf01c39a2b
00000487-1e6c-4d6d-a683-6f11d517962c
000004cc-6359-4a9a-aa2a-70a6b73a06b1
00000536-37ee-471c-a8e0-3d233b8102f5
Now i need to use this table in aws DMS which accepts only query like select * from table where column =,<=,>=
My use case is to find the exact location of the millions of GUID so that i can divide table into multiple query and select based on GUID .
For example if we have 100th GID is 00000536-37ee-471c-a8e0-3d233b8102f5 then i can write query like select * from my table where GUID <=100
The limitation is i can not add any new columns in the existing table because application impact is huge .
How can i do this ?
One Option that i thought but wanted to confirm is below
Create a temp table
Temp table will have auto generated sequence and ID column
Inset into temp table select only GUID from main table with order of GUID .
In this case the value will be stored on order and i an first select GUID based on 100th number and then i can pass that GUID and write my oroginal query
But i am not sure whether this will work on not
Can some one suggest on this or suggest some other option ?
So let me explain what i want .
I want DMS to read may main table in parallel and migrate .
So lets say one DMS task can read nd migrate from 1 to 100,another 100 to 200 another >200 like that .
Currently i can not do because we dont know the position of the primary key and write the query .
If you want to divide your table into chunks of equal sizes, I would take advantage of the hexadecimal nature of the GUIDs. It will be 256 instead of 100 chunks, but this might be acceptable.
CREATE TABLE t (pk VARCHAR2(36) PRIMARY KEY);
INSERT INTO t VALUES ('000000bd-104e-4fd6-a791-c5422f29e1b5');
The easiest option would be
SELECT * FROM t WHERE pk LIKE '%b5';
A bit more advanced:
SELECT pk, to_number(substr(pk, -2),'xx') FROM t;
If you have millions of rows, this is probably faster:
ALTER TABLE t ADD (mycol GENERATED ALWAYS AS (to_number(substr(pk, -2),'xx')));
CREATE INDEX i ON t(mycol);
SELECT * FROM t WHERE mycol=181;
Once your migration is done, you can undo the additional virtual column:
DROP INDEX i;
ALTER TABLE t DROP (mycol);
I've recently started to play around with Cassandra. My understanding is that in a Cassandra table you define 2 keys, which can be either single column or composites:
The Partitioning Key: determines how to distribute data across nodes
The Clustering Key: determines in which order the records of a same partitioning key (i.e. within a same node) are written. This is also the order in which the records will be read.
Data from a table will always be sorted in the same order, which is the order of the clustering key column(s). So a table must be designed for a specific query.
But what if I need to perform 2 different queries on the data from a table. What is the best way to solve this when using Cassandra ?
Example Scenario
Let's say I have a simple table containing posts that users have written :
CREATE TABLE posts (
username varchar,
creation timestamp,
content varchar,
PRIMARY KEY ((username), creation)
);
This table was "designed" to perform the following query, which works very well for me:
SELECT * FROM posts WHERE username='luke' [ORDER BY creation DESC];
Queries
But what if I need to get all posts regardless of the username, in order of time:
Query (1): SELECT * FROM posts ORDER BY creation;
Or get the posts in alphabetical order of the content:
Query (2): SELECT * FROM posts WHERE username='luke' ORDER BY content;
I know that it's not possible given the table I created, but what are the alternatives and best practices to solve this ?
Solution Ideas
Here are a few ideas spawned from my imagination (just to show that at least I tried):
Querying with the IN clause to select posts from many users. This could help in Query (1). When using the IN clause, you can fetch globally sorted results if you disable paging. But using the IN clause quickly leads to bad performance when the number of usernames grows.
Maintaining full copies of the table for each query, each copy using its own PRIMARY KEY adapted to the query it is trying to serve.
Having a main table with a UUID as partitioning key. Then creating smaller copies of the table for each query, which only contain the (key) columns useful for their own sort order, and the UUID for each row of the main table. The smaller tables would serve only as "sorting indexes" to query a list of UUID as result, which can then be fetched using the main table.
I'm new to NoSQL, I would just want to know what is the correct/durable/efficient way of doing this.
The SELECT * FROM posts ORDER BY creation; will results in a full cluster scan because you do not provide any partition key. And the ORDER BY clause in this query won't work anyway.
Your requirement I need to get all posts regardless of the username, in order of time is very hard to achieve in a distributed system, it supposes to:
fetch all user posts and move them to a single node (coordinator)
order them by date
take top N latest posts
Point 1. require a full table scan. Indeed as long as you don't fetch all records, the ordering can not be achieve. Unless you use Cassandra clustering column to order at insertion time. But in this case, it means that all posts are being stored in the same partition and this partition will grow forever ...
Query SELECT * FROM posts WHERE username='luke' ORDER BY content; is possible using a denormalized table or with the new materialized view feature (http://www.doanduyhai.com/blog/?p=1930)
Question 1:
Depending on your use case I bet you could model this with time buckets, depending on the range of times you're interested in.
You can do this by making the primary key a year,year-month, or year-month-day depending on your use case (or finer time intervals)
The basic idea is that you bucket changes for what suites your use case. For example:
If you often need to search these posts over months in the past, then you may want to use the year as the PK.
If you usually need to search the posts over several days in the past, then you may want to use a year-month as the PK.
If you usually need to search the post for yesterday or a couple of days, then you may want to use a year-month-day as your PK.
I'll give a fleshed out example with yyyy-mm-dd as the PK:
The table will now be:
CREATE TABLE posts_by_creation (
creation_year int,
creation_month int,
creation_day int,
creation timeuuid,
username text, -- using text instead of varchar, they're essentially the same
content text,
PRIMARY KEY ((creation_year,creation_month,creation_day), creation)
)
I changed creation to be a timeuuid to guarantee a unique row for each post creation event. If we used just a timestamp you could theoretically overwrite an existing post creation record in here.
Now we can then insert the Partition Key (PK): creation_year, creation_month, creation_day based on the current creation time:
INSERT INTO posts_by_creation (creation_year, creation_month, creation_day, creation, username, content) VALUES (2016, 4, 2, now() , 'fromanator', 'content update1';
INSERT INTO posts_by_creation (creation_year, creation_month, creation_day, creation, username, content) VALUES (2016, 4, 2, now() , 'fromanator', 'content update2';
now() is a CQL function to generate a timeUUID, you would probably want to generate this in the application instead, and parse out the yyyy-mm-dd for the PK and then insert the timeUUID in the clustered column.
For a usage case using this table, let's say you wanted to see all of the changes today, your CQL would look like:
SELECT * FROM posts_by_creation WHERE creation_year = 2016 AND creation_month = 4 AND creation_day = 2;
Or if you wanted to find all of the changes today after 5pm central:
SELECT * FROM posts_by_creation WHERE creation_year = 2016 AND creation_month = 4 AND creation_day = 2 AND creation >= minTimeuuid('2016-04-02 5:00-0600') ;
minTimeuuid() is another cql function, it will create the smallest possible timeUUID for the given time, this will guarantee that you get all of the changes from that time.
Depending on the time spans you may need to query a few different partition keys, but it shouldn't be that hard to implement. Also you would want to change your creation column to a timeuuid for your other table.
Question 2:
You'll have to create another table or use materialized views to support this new query pattern, just like you thought.
Lastly if your not on Cassandra 3.x+ or don't want to use materialized views you can use Atomic batches to ensure data consistency across your several de-normalized tables (that's what it was designed for). So in your case it would be a BATCH statement with 3 inserts of the same data to 3 different tables that support your query patterns.
The solution is to create another tables to support your queries.
For SELECT * FROM posts ORDER BY creation;, you may need some special column for grouping it, maybe by month and year, e.g. PRIMARY KEY((year, month), timestamp) this way the cassandra will have a better performance on read because it doesn't need to scan the whole cluster to get all data, it will also save the data transfer between nodes too.
Same as SELECT * FROM posts WHERE username='luke' ORDER BY content;, you must create another table for this query too. All column may be same as your first table but with the different Primary Key, because you cannot order by the column that is not the clustering column.
I have a table that I expect to get 7 million records a month on a pretty wide table. A small portion of these records are expected to be flagged as "problem" records.
What is the best way to implement the table to locate these records in an efficient way?
I'm new to Oracle, but is a materialized view an valid option? Are there such things in Oracle such as indexed views or is this potentially really the same thing?
Most of the reporting is by month, so partitioning by month seems like an option, but a "problem" record may be lingering for several months theorectically. Otherwise, the reporting shuold be mostly for the current month. Would you expect that querying across all month partitions to locate any problem record would cause significant performance issues compared to usinga single table?
Your general thoughts of where to start would be appreciated. I realize I need to read up and I'll do that but I wanted to get the community thought first to make sure I read the right stuff.
One more thought: The primary key is a GUID varchar2(36). In order of magnitude, how much of a performance hit would you expect this to be relative to using a NUMBER data type PK? This worries me but it is out of my control.
It depends what you mean by "flagged", but it sounds to me like you would benefit from a simple index, function based index, or an indexed virtual column.
In all cases you should be careful to ensure that all the index columns are NULL for rows that do not need to be flagged. This way your index will contain only the rows that are flagged (Oracle does not - by default - index rows in B-Tree indexes where all index column values are NULL).
Your primary key being a VARCHAR2 GUID should make no difference, at least with regards to the specific flagging of rows in this question, indexes will point to rows via Oracle internal ROWIDs.
Indexes support partitioning, so if your data is already partitioned, your index could be set to match.
Simple column index method
If you can dictate how the flagging works, or the column already exists, then I would simply add an index to it like so:
CREATE INDEX my_table_problems_idx ON my_table (problem_flag)
/
Function-based index method
If the data model is fixed / there is no flag column, then you can create a function-based index assuming that you have all the information you need in the target table. For example:
CREATE INDEX my_table_problems_fnidx ON my_table (
CASE
WHEN amount > 100 THEN 'Y'
ELSE NULL
END
)
/
Now if you use the same logic in your SELECT statement, you should find that it uses the index to efficiently match rows.
SELECT *
FROM my_table
WHERE CASE
WHEN amount > 100 THEN 'Y'
ELSE NULL
END IS NOT NULL
/
This is a bit clunky though, and it requires you to use the same logic in queries as the index definition. Not great. You could use a view to mask this, but you're still duplicating logic in at least two places.
Indexed virtual column
In my opinion, this is the best way to do it if you are computing the value dynamically (available from 11g onwards):
ALTER TABLE my_table
ADD virtual_problem_flag VARCHAR2(1) AS (
CASE
WHEN amount > 100 THEN 'Y'
ELSE NULL
END
)
/
CREATE INDEX my_table_problems_idx ON my_table (virtual_problem_flag)
/
Now you can just query the virtual column as if it were a real column, i.e.
SELECT *
FROM my_table
WHERE virtual_problem_flag = 'Y'
/
This will use the index and puts the function-based logic into a single place.
Create a new table with just the pks of the problem rows.
I need to query table1 find all orders and created date ( key is order number an date)).
In table 2 ( key is order number an date) Check if the order exists for a a date.
For this i am scanning table 1 and for each record checking if it exists in table 2. Any better way to do this
In this situation in which your key is identical for both tables, it makes sense to have a single table in which you store both data for Table 1 and Table 2. In that way you can do a single scan on your data and know straight away if the data exists for both criteria.
Even more so, if you want to use this data in MapReduce, you would simply scan that single table. If you only want to get the relevant rows, you could define a filter on the Scan. For example, in the case where you will not be populating rows at all in Table 2, you would simply use a ColumnPrefixFilter
If, however, you do need to keep this data separately in 2 tables, you could pre-split the tables with the same region boundaries for both tables - this will be helpful when you do the query that you are aiming for - load all rows in Table 1 when row exists in Table 2. Essentially this would be a map-side join. You could define multiple inputs in your MapReduce job, and since the region borders are the same, the splits will be such that each mapper will have corresponding rows from both tables. You would probably need to implement your own MultipleInput format for that (the MultiTableInputFormat class recently introduced in 0.96 does not seem to do that map side join)
I recently was reading about Oracle Index Organized Tables (IOTs) but am not sure I quite understand WHEN to use them. So I have a small table:
create table categories
(
id VARCHAR2(36),
group VARCHAR2(100),
category VARCHAR2(100
)
create unique index (group, category, id) COMPRESS 2;
The id column is a foreign key from another table entries and my common query is:
select e.id, e.time, e.title from entries e, categories c where e.id=c.id AND e.group=? AND c.category=? ORDER by e.time
The entries table is indexed properly.
Both of these tables have millions (16M currently) of rows and currently this query really stinks (note: I have it wrapped in a pagination query also so I only get back the first 20, but for simplicity I omitted that).
Since I am basically indexing the entire table, does it make sense to create this table as an IOT?
EDIT by popular demand:
create table entries
(
id VARCHAR2(36),
time TIMESTAMP,
group VARCHAR2(100),
title VARCHAR2(500),
....
)
create index (group, time) compress 1;
My real question I dont think depends on this though. Basically if you have a table with few columns (3 in this example) and you are planning on putting a composite index on all three rows is there any reason not to use an IOT?
IOTs are great for a number of purposes, including this case where you're gonna have an index on all (or most) of the columns anyway - but the benefit only materialises if you don't have the extra index - the idea is that the table itself is an index, so put the columns in the order that you want the index to be in. In your case, you're accessing category by id, so it makes sense for that to be the first column. So effectively you've got an index on (id, group, category). I don't know why you'd want an additional index on (group, category, id).
Your query:
SELECT e.id, e.time, e.title
FROM entries e, categories c
WHERE e.id=c.id AND e.group=? AND c.category=?
ORDER by e.time
You're joining the tables by ID, but you have no index on entries.id - so the query is probably doing a hash or sort merge join. I wouldn't mind seeing a plan for what your system is doing now to confirm.
If you're doing a pagination query (i.e. only interested in a small number of rows) you want to get the first rows back as quick as possible; for this to happen you'll probably want a nested loop on entries, e.g.:
NESTED LOOPS
ACCESS TABLE BY ROWID - ENTRIES
INDEX RANGE SCAN - (index on ENTRIES.group,time)
ACCESS TABLE BY ROWID - CATEGORIES
INDEX RANGE SCAN - (index on CATEGORIES.ID)
Since the join to CATEGORIES is on ID, you'll want an index on ID; if you make it an IOT, and make ID the leading column, that might be sufficient.
The performance of the plan I've shown above will be dependent on how many rows match the given "group" - i.e. how selective an average "group" is.
Have you looked at dba-oracle.com, asktom.com, IOUG, another asktom.com?
There are penalties to pay for IOTs - e.g., poorer insert performance
Can you prototype it and compare performance?
Also, perhaps you might want to consider a hash cluster.
IOT's are a trade off. You are getting access performance for decreased insert/update performance. We typically use them for reference data that is batch loaded daily and not updated during the day. This is not to say it's the only way to use them, just how we use them.
Few things here:
You mention pagination - have you considered the first_rows hint?
Is that the order your index is in, with group as the first field? If so I'd consider moving ID to be the first column since that index will not be used.
foreign keys should have an index on the column. Consider addind an index on the foreign key (id column).
Are you sure it's not the ORDER BY causing slowness?
What version of Oracle are you using?
I ASSUME there is a primary key on table entries for field id, correct?
Why the WHERE condition does not include "c.group = e.group" ?
Try to:
Remove the order by condition
Change the index definition from "create unique index (group,
category, id)" to "create unique index (id, group, category)"
Reorganise table categories as an IOT on (group, category, id)
Reorganise table categories as an IOT on (id, group, category)
In each of the above case use EXPLAIN PLAN to review the cost