pyspark dataframe joining of two dataframe
I have two dataframes say df1 and df2:
df1 has fields as CI_NAME,CLOSE_TIME,CH_ID
and df2 has fields as NAME,TIMESTAMP,MEM_CONSUMED.
Basically df1 has records of software updates done to the system and df2 has monitoring records of the system.
I need to add a field in df1 named cpu_util_avg_before_update by comparing CI_NAME equal to NAME field of df2 and CLOSE_TIME between TIMESTAMP - 7 days and TIMESTAMP and then take the average of MEM_CONSUMED.
How can I do that, any help would be appreciated as I have tried udf but that is not taking dataframe as input.
Thanks
here is the code that I tried:
from pyspark.sql.functions import col,udf,struct
from dateutil import parser
import datetime
@udf
def memavgbeforeupdate(structx,df2):
df=df2.where(col("name")==structx[1] & (col("timestamp")>parser.parse(structx[0])-datetime.timedelta(days=10) & col("timestamp")<parser.parse(structx[0])+datetime.timedelta(days=10)))
df=df.where(col("mem_consumed_average")!="NaN").where(col("mem_consumed_average").isNotNull())
if df.rdd.isEmpty():
return -1
else:
df1=df.select("mem_consumed_average")
return float(str(df1.select(mean(col("mem_consumed_average"))).collect()[0]).split("=")[1].split(")")[0])
df3=df1.withColumn("mem_avg_before_update",memavgbeforeupdate(struct(col("CLOSE_TIME"),col("CI_NAME")),df2))
But that's not working and throwing error as:
'DataFrame' object has no attribute '_get_object_id'
apache-spark dataframe pyspark data-science
asked Nov 22 '18 at 12:52
Neeraj KumarNeeraj Kumar
62
add a comment |
I have two dataframes say df1 and df2:
df1 has fields as CI_NAME,CLOSE_TIME,CH_ID
and df2 has fields as NAME,TIMESTAMP,MEM_CONSUMED.
Basically df1 has records of software updates done to the system and df2 has monitoring records of the system.
I need to add a field in df1 named cpu_util_avg_before_update by comparing CI_NAME equal to NAME field of df2 and CLOSE_TIME between TIMESTAMP - 7 days and TIMESTAMP and then take the average of MEM_CONSUMED.
How can I do that, any help would be appreciated as I have tried udf but that is not taking dataframe as input.
Thanks
here is the code that I tried:
from pyspark.sql.functions import col,udf,struct
from dateutil import parser
import datetime
@udf
def memavgbeforeupdate(structx,df2):
df=df2.where(col("name")==structx[1] & (col("timestamp")>parser.parse(structx[0])-datetime.timedelta(days=10) & col("timestamp")<parser.parse(structx[0])+datetime.timedelta(days=10)))
df=df.where(col("mem_consumed_average")!="NaN").where(col("mem_consumed_average").isNotNull())
if df.rdd.isEmpty():
return -1
else:
df1=df.select("mem_consumed_average")
return float(str(df1.select(mean(col("mem_consumed_average"))).collect()[0]).split("=")[1].split(")")[0])
df3=df1.withColumn("mem_avg_before_update",memavgbeforeupdate(struct(col("CLOSE_TIME"),col("CI_NAME")),df2))
But that's not working and throwing error as:
'DataFrame' object has no attribute '_get_object_id'
apache-spark dataframe pyspark data-science
asked Nov 22 '18 at 12:52
Neeraj KumarNeeraj Kumar
62
You cannot useDataFrameinudf. You'll have to rewrite this as a combination of joins and aggregations. Could you please provide edit your question and provide reproducible example?
– user10465355
Nov 22 '18 at 20:17
add a comment |
I have two dataframes say df1 and df2:
df1 has fields as CI_NAME,CLOSE_TIME,CH_ID
and df2 has fields as NAME,TIMESTAMP,MEM_CONSUMED.
Basically df1 has records of software updates done to the system and df2 has monitoring records of the system.
I need to add a field in df1 named cpu_util_avg_before_update by comparing CI_NAME equal to NAME field of df2 and CLOSE_TIME between TIMESTAMP - 7 days and TIMESTAMP and then take the average of MEM_CONSUMED.
How can I do that, any help would be appreciated as I have tried udf but that is not taking dataframe as input.
Thanks
here is the code that I tried:
from pyspark.sql.functions import col,udf,struct
from dateutil import parser
import datetime
@udf
def memavgbeforeupdate(structx,df2):
df=df2.where(col("name")==structx[1] & (col("timestamp")>parser.parse(structx[0])-datetime.timedelta(days=10) & col("timestamp")<parser.parse(structx[0])+datetime.timedelta(days=10)))
df=df.where(col("mem_consumed_average")!="NaN").where(col("mem_consumed_average").isNotNull())
if df.rdd.isEmpty():
return -1
else:
df1=df.select("mem_consumed_average")
return float(str(df1.select(mean(col("mem_consumed_average"))).collect()[0]).split("=")[1].split(")")[0])
df3=df1.withColumn("mem_avg_before_update",memavgbeforeupdate(struct(col("CLOSE_TIME"),col("CI_NAME")),df2))
But that's not working and throwing error as:
'DataFrame' object has no attribute '_get_object_id'
apache-spark dataframe pyspark data-science
asked Nov 22 '18 at 12:52
Neeraj KumarNeeraj Kumar
62
I have two dataframes say df1 and df2:
df1 has fields as CI_NAME,CLOSE_TIME,CH_ID
and df2 has fields as NAME,TIMESTAMP,MEM_CONSUMED.
Basically df1 has records of software updates done to the system and df2 has monitoring records of the system.
I need to add a field in df1 named cpu_util_avg_before_update by comparing CI_NAME equal to NAME field of df2 and CLOSE_TIME between TIMESTAMP - 7 days and TIMESTAMP and then take the average of MEM_CONSUMED.
How can I do that, any help would be appreciated as I have tried udf but that is not taking dataframe as input.
Thanks
here is the code that I tried:
from pyspark.sql.functions import col,udf,struct
from dateutil import parser
import datetime
@udf
def memavgbeforeupdate(structx,df2):
df=df2.where(col("name")==structx[1] & (col("timestamp")>parser.parse(structx[0])-datetime.timedelta(days=10) & col("timestamp")<parser.parse(structx[0])+datetime.timedelta(days=10)))
df=df.where(col("mem_consumed_average")!="NaN").where(col("mem_consumed_average").isNotNull())
if df.rdd.isEmpty():
return -1
else:
df1=df.select("mem_consumed_average")
return float(str(df1.select(mean(col("mem_consumed_average"))).collect()[0]).split("=")[1].split(")")[0])
df3=df1.withColumn("mem_avg_before_update",memavgbeforeupdate(struct(col("CLOSE_TIME"),col("CI_NAME")),df2))
But that's not working and throwing error as:
'DataFrame' object has no attribute '_get_object_id'
apache-spark dataframe pyspark data-science
apache-spark dataframe pyspark data-science
asked Nov 22 '18 at 12:52
Neeraj KumarNeeraj Kumar
62
asked Nov 22 '18 at 12:52
Neeraj KumarNeeraj Kumar
62
edited Nov 25 '18 at 18:33
Neeraj Kumar
asked Nov 22 '18 at 12:52
Neeraj KumarNeeraj Kumar
62
asked Nov 22 '18 at 12:52
Neeraj KumarNeeraj Kumar
62
asked Nov 22 '18 at 12:52
Neeraj KumarNeeraj Kumar
62
62
You cannot useDataFrameinudf. You'll have to rewrite this as a combination of joins and aggregations. Could you please provide edit your question and provide reproducible example?
– user10465355
Nov 22 '18 at 20:17
add a comment |
You cannot useDataFrameinudf. You'll have to rewrite this as a combination of joins and aggregations. Could you please provide edit your question and provide reproducible example?
– user10465355
Nov 22 '18 at 20:17
You cannot use
DataFrame in udf. You'll have to rewrite this as a combination of joins and aggregations. Could you please provide edit your question and provide reproducible example?– user10465355
Nov 22 '18 at 20:17
You cannot use
DataFrame in udf. You'll have to rewrite this as a combination of joins and aggregations. Could you please provide edit your question and provide reproducible example?– user10465355
Nov 22 '18 at 20:17
add a comment |
0
active
oldest
votes
Your Answer
StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53431481%2fpyspark-dataframe-joining-of-two-dataframe%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
0
active
oldest
votes
0
active
oldest
votes
active
oldest
votes
active
oldest
votes
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53431481%2fpyspark-dataframe-joining-of-two-dataframe%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
You cannot use
DataFrameinudf. You'll have to rewrite this as a combination of joins and aggregations. Could you please provide edit your question and provide reproducible example?– user10465355
Nov 22 '18 at 20:17