I have two tables like below. Basically i want to join both of them and expected the result like below.
First 3 rows of table 2 does not have any activity id just empty.
All fields are tab separated. Category "33" is having three description as per table 2.
We need to make use of "Activity ID" to get the result for "33" category as there are 3 values for that.
could anyone tell me how to achieve this output?
TABLE: 1
Empid Category ActivityID
44126 33 TRAIN
44127 10 UFL
44128 12 TOI
44129 33 UNASSIGNED
44130 15 MICROSOFT
44131 33 BENEFITS
44132 43 BENEFITS
TABLE 2:
Category ActivityID Categdesc
10 billable
12 billable
15 Non-billable
33 TRAIN Training
33 UNASSIGNED Bench
33 BENEFITS Benefits
43 Benefits
Expected Output:
44126 33 Training
44127 10 Billable
44128 12 Billable
44129 33 Bench
44130 15 Non-billable
44131 33 Benefits
44132 43 Benefits
It's little difficult to do this Hive as there are many limitations. This is how I solved it but there could be a better way.
I named your tables as below.
Table1 = EmpActivity
Table2 = ActivityMas
The challenge comes due to the null fields in Table2. I created a view and Used UNION to combine result from two distinct queries.
Create view actView AS Select * from ActivityMas Where Activityid ='';
SELECT * From (
Select EmpActivity.EmpId, EmpActivity.Category, ActivityMas.categdesc
from EmpActivity JOIN ActivityMas
ON EmpActivity.Category = ActivityMas.Category
AND EmpActivity.ActivityId = ActivityMas.ActivityId
UNION ALL
Select EmpActivity.EmpId, EmpActivity.Category, ActView.categdesc from EmpActivity
JOIN ActView ON EmpActivity.Category = ActView.Category
)
You have to use top level SELECT clause as the UNION ALL is not directly supported from top level statements. This will run total 3 MR jobs. ANd below is the result I got.
44127 10 billable
44128 12 billable
44130 15 Non-billable
44132 43 Benefits
44131 33 Benefits
44126 33 Training
44129 33 Bench
I'm not sure if I understand your question or your data, but would this work?
select table1.empid, table1.category, table2.categdesc
from table1 join table2
on table1.activityID = table2.activityID;
Related
I have a table that looks like so:
Name Age Num_Hobbies Num Shoes
Jane 31 10 2
Bob 23 3 4
Jane 60 2 200
Jane 31 100 6
Bob 10 8 7
etc etc
I would like to group this table by Name and Age, and at random pick one row from the rest of the columns.
In pandas, I would do the following:
df.groupby(['Name', 'Age']).apply(lambda x: x.sample(n=1))
In hive, I know how to create the group, but not how to choose a single random sample from group.
I saw this question on stack overflow: How to sample for each group in hive?
However, I do not understand how to apply Dynamic partitions or Hive bucketing to select a single sample from a group.
You can use rank() or row_number() with rand()
select * from
(
select name,age,rank() (partition by name,age order by rand()) as rank
from table
) t
where rank = 1
I have been working with an application that is integrated with spring and Hibernate 4.X.X and its transaction is managed by JTA in Weblogic application server. After 3 years, there are about 40 million records only into one table from 100 tables that exist in my DB. The DB is Oracle 11g. The response time of a query is about 5 minutes because of increasing the count of records of this tables.
I customized the query and put it into Sql Developer and run the query advisor plan for suggestion some Index. Totally after doing such this, its response time is reduced to 2 minute. But even so, this response time does not satisfy the Custumer. To further clarify I put the query, It is as following:
select *
from (select (count(storehouse0_.ID) over()) as col_0_0_,
storehouse3_.storeHouse_ID as col_1_0_,
(DBPK_PUB_STOREHOUSE.get_Storehouse_Title(storehouse5_.id, 1)) as col_2_0_,
storehouse5_.Organization_Code as col_3_0_,
publicgood1_.Goods_Item_Id as col_4_0_,
storehouse0_.storeHouse_Inventory_Id as col_5_0_,
storehouse0_.Id as col_6_0_,
storehouse3_.samapel_Item_Id as col_7_0_,
samapelite10_.MAINNAME as col_8_0_,
publicgood1_.serial_Number as col_9_0_,
publicgood1_1_.production_Year as col_10_0_,
samapelpar2_.ID_SourceInfo as col_11_0_,
samapelpar2_.Pn as col_12_0_,
storehouse3_.expire_Date as col_13_0_,
publicgood1_1_.Status_Id as col_14_0_,
baseinform12_.Topic as col_15_0_,
publicgood1_.public_Num as col_16_0_,
cast(publicgood1_1_.goods_Status as number(10, 0)) as col_17_0_,
publicgood1_1_.goods_Status as col_18_0_,
publicgood1_1_.deleted as col_19_0_
from amd.Core_StoreHouse_Inventory_Item storehouse0_,
amd.Core_STOREHOUSE_INVENTORY storehouse3_,
amd.Core_STOREHOUSE storehouse5_,
amd.SMP_SAMAPEL_CODE samapelite10_
cross join amd.Core_Goods_Item_Public publicgood1_
inner join amd.Core_Goods_Item publicgood1_1_
on publicgood1_.Goods_Item_Id = publicgood1_1_.Id
left outer join amd.SMP_SOURCEINFO samapelpar2_
on publicgood1_1_.Samapel_Part_Number_Id =
samapelpar2_.ID_SourceInfo, amd.App_BaseInformation
baseinform12_
where not exists
(select ssec.samapelITem_id
from core_security_samapelitem ssec
inner join core_goods_item g
on ssec.samapelitem_id = g.samapel_item_id
where not exists (SELECT aa.groupid
FROM app_actiongroup aa
where aa.groupid in
(select au.groupid
from app_usergroup au
where au.userid = 1)
and aa.actionid = 9054)
and ssec.isenable = 1
and storehouse0_.goods_Item_ID = g.id)
and not exists
(select *
from CORE_POWER_SECURITY cps
where not exists (SELECT aa.groupid
FROM app_actiongroup aa
where aa.groupid in
(select au.groupid
from app_usergroup au
where au.userid = 1)
and aa.actionid = 9055)
and cps.inventory_id =
storehouse0_.storeHouse_Inventory_Id
and cps.goodsitemtype = 6)
and storehouse0_.storeHouse_Inventory_Id = storehouse3_.Id
and storehouse3_.storeHouse_ID = storehouse5_.Id
and storehouse3_.samapel_Item_Id = samapelite10_.MAINCODE
and publicgood1_1_.Status_Id = baseinform12_.ID
and 1 <> 2
and storehouse0_.goods_Item_ID = publicgood1_.Goods_Item_Id
and publicgood1_1_.edited = 0
and publicgood1_1_.deleted = 0
and (exists (select storehouse13_.Id
from amd.Core_STOREHOUSE storehouse13_
cross join amd.core_power power16_
cross join amd.core_power power17_
where storehouse5_.powerID = power16_.Id
and storehouse13_.powerID = power17_.Id
and (storehouse13_.Id in (741684217))
and storehouse13_.storeHouseType = 2
and (power16_.hierarchiCode like
power17_.hierarchiCode || '%')) or
(storehouse3_.storeHouse_ID in (741684217)) and
storehouse5_.storeHouseType = 1)
and (storehouse5_.storeHouse_Status not in (2, 3))
order by storehouse3_.samapel_Item_Id)
where rownum <= 10
[Note: This query is generated by Hibernate].
It is clear that order by 40 million holds so much time.
I find the main issue of this query. I omitted the “order by” and run the query, its response time was reduced to about 5 second. I was wonderful why the “order by” affects so much the response time.
(Some body may think that if this table is partitioned or use another facility of oracle, it may get better response time. Ok it may be right but my emphasis is the “order by” performance. If there is a way that do the “order by” responsibility, why not to do it). Any way I am not able to omit the “order by” because the Customer needs to order and it is necessary for paging. I find a solution that is explained by an example. This solution I order only some records that is needed. How, I will explain later. It is clear when oracle wants to sort 40 million records, it naturally takes so much time. I replace “order by” with “where clause”. With doing this replacement the response time was reduces from 2 minute to about 5 second and this is very exciting for me.
I explain my solution via an example, anybody that read this Post tells me whether this solution is good or there are another solution that I do not know exists.
Another hand I have a solution that is explained later, if it is ok or not. Whether I use it or not.
I explain my solution:
Let’s assumed that there are two table as below:
Post table
Id Others fields
1
2
3
4
5
… …
Post_comment table
Id post_id
1 5
2 5
3 5
4 5
6 5
7 2
8 2
9 2
10 3
11 1
12 1
13 1
14 1
15 1
16 1
17 1
18 1
19 1
20 1
21 1
22 1
23 1
24 1
25 1
26 4
27 4
There is a form that shows the result of join between POST table and POST_COMMENT table.
I explain both query with “order by” all records of that table and “order by” only specific records that are needed. The result of two query are exactly the same but the response time of second approach is the better than that one.
You assume that the page size is 10 and you are in page 3.
The first query with the “order by” all records of that table:
select *
from (Select res.*, rownum as rownum_
from (Select * from POST_COMMENT Order by post_id asc) res
Where rownum <= 30)
where rownum_ > 20
The second solution:
Before execution the query, I query as below:
select *
from (select post_id, count(id) from POST_COMMENT group by post_id)
order by post_id asc
So the result of it is the below:
Post_id Count(id) Sum(count(id))
1 15 15
2 3 18
3 1 19
4 2 21
5 5 26
It needs to say that the third column that is "Sum(count(id))" is calculated after that query.Any entry of this column is sum all before records.
So there is a formula that specifics which post_id must be selected. The formula is the below:
pageSize = 10, pageNumber = 3
from : (pageNumber – 1) * pageCount 2 * 10 = 20
to : (pageNumber – 1) * pageCount + pageCount 20 + 10 = 30
So I need the posts that are between (20, 30] of Sum(count(id)). According to this, I need only two post_id that have value 4,5. According to this the main query of second approach is:
select *
from (select rownum as rownum_, res.*
from (select *
from (select * from POST_COMMENT where post_id in (4, 5))
order by post_id asc) res
where rownum <= 30)
where rownum_ > 20
If you look at both query, you will see the biggest difference. The second query only selects the records of POST_COMENT that have post_id that are 4 and 5. After that, orders this records not all records of that table.
After posting this post, I have searched. finally I am redirected to HERE . I can reach to the response time that is very excited for me. It is reduced from 3 minutes to less than 3 seconds. It is necessary to know, I only use one tip from all of the query optimization guidelines that are in that site that is Duplicate constant condition for different tables whenever possible.
Note: Before doing this tip, there are some indexs on fields that are in where-clause and order-by.
I am currently using the below query to pull the data which is being represented in 4 rows for the same sample record and would like to have it flattened into 1 ow per sample. Attaching the query results for information any help is much appreciated.
select s.name as CRF, a.name as Aliquot_Name, a.aliquot_type, au.u_step_yield as Step_Yield, au.u_step_concentration as Step_Concentration, au. u_pooled_plasma_volume as Pooled_Plasma_volume
from aliquot a
join aliquot_user au on a.aliquot_id = au.aliquot_id
join sample s on s.sample_id = a.SAMPLE_ID
where a.aliquot_type in ('DNA Extracted', 'Library', 'Target Enrichment', 'DNA Plasma')
order by s.name desc, a.aliquot_type, a.name, au.u_step_yield, au.u_step_concentration, au.u_pooled_plasma_volume;
CRF ALIQUOT_NAME ALIQUOT_TYPE STEP_YIELD STEP_CONCENTRATION POOLED_PLASMA_VOLUME
CRF007650 PE-0046758 DNA Plasma 10
CRF007650 LCNL-47275 Library 2,178 36
CRF007650 HCNLS-47467 Target Enrichment 105 2
CRF007649 1146667362 DNA Extracted 451 6
CRF007649 PE-0046774 DNA Plasma 10
CRF007649 LCNL-47291 Library 3,543 59
CRF007649 HCNLS-47483 Target Enrichment 132 2
CRF007648 1146668498 DNA Extracted 166 2
CRF007648 PE-0046755 DNA Plasma 9
CRF007648 LCNL-47272 Library 3,881 65
CRF007648 HCNLS-47463 Target Enrichment 381 6
CRF007647 1146635220 DNA Extracted 29 0
CRF007647 PE-0046764 DNA Plasma 8
CRF007647 LCNL-47281 Library 1,274 21
CRF007647 HCNLS-47473 Target Enrichment 57 1
CRF007646 1146736347 DNA Extracted 67 1
I think you have to more specific.
There's no tables' info. which is pk and which is not.
Only I can say now is that you have to join same table if you want to flatten rows.
If you want to get answer with query, you have to write your tables' info and others can help people answer your question.
As far as I understand your data you have 4 entrys in your table a with different a.aliquot_type ('DNA Extracted', 'Library', 'Target Enrichment', 'DNA Plasma'). And you want to give 4 columns with the corresponding Aliquot_Name (one for 'DNA Extracted' etc.).
You could use 4 columns with a subselect where you read the corresponding data from aliquot and therefore you have to quit the join
a.aliquot_id = au.aliquot_id
For example:
select s.name as CRF, (select a.aliquot_type from aliquot where a.aliquot_type = 'DNA Extracted' and ....) col1, (select a.aliquot_type from aliquot where a.aliquot_type = 'Library' and ....) col2, ...
I have two tables affiliation and customer, in that i have data like this
aff_id From_cus_id
------ -----------
1 10
2 20
3 30
4 40
5 50
cust_id cust_aff_id
------- -------
10
20
30
40
50
i need to update data for cust_aff_id column from affiliation table which is aff_id like below
cust_id cust_aff_id
------- -------
10 1
20 2
30 3
40 4
50 5
could u please give reply if anyone knows......
Oracle doesn't have an UPDATE with join syntax, but you can use a subquery instead:
UPDATE customer
SET customer.cust_aff_id =
(SELECT aff_id FROM affiliation WHERE From_cus_id = customer.cust_id)
merge into customer t2
using affiliation t1 on (t1.From_cus_id =t2.cust_id )
WHEN MATCHED THEN
update set t2.cust_aff_id = t1.aff_id
;
Here is an update with join syntax. This, quite reasonably, works only if from_cus_id is primary key in the first table and cust_id is foreign key in the second table, referencing the first table. Without these conditions, the requirement doesn't make much sense in the first place anyway... but Oracle requires that these constraints be stated explicitly in the tables. This is also reasonable on Oracle's part IMO.
update
( select t1.aff_id, t2.cust_aff_id
from affiliation t1 join customer t2 on t2.cust_id = t1.from_cus_id) j
set j.cust_aff_id = j.aff_id;
For data like below
Col1
----
1
23
34
124
Output should be like below
Out
1
2
3
4
I tried the below hierarchical query but its giving repeated data
select substr(col1, level, 1)
from table1
connect by level <= length(col1);
I can't use distinct as this is sample and main table where I have to use this query has quite large data.
Thanks