scala forward reference extends over definition of value dataframe
I'm trying to typecast the columns in the data frame df_trial
which has all the columns as string, based on an XML file I'm trying to type cast each column.
val columnList = sXml \ "COLUMNS" "COLUMN"
val df_trial = sqlContext.createDataFrame(rowRDD, schema_allString)
columnList.foreach(i =>
var columnName = (i \ "@ID").text.toLowerCase()
var dataType = (i \ "@DATA_TYPE").text.toLowerCase()
if (dataType == "number")
print("number")
var DATA_PRECISION: Int = (i \ "@DATA_PRECISION").text.toLowerCase().toInt
var DATA_SCALE: Int = (i \ "@DATA_SCALE").text.toLowerCase().toInt;
var decimalvalue = "decimal(" + DATA_PRECISION + "," + DATA_SCALE + ")"
val df_intermediate: DataFrame =
df_trial.withColumn(s"$columnName",
col(s"$columnName").cast(s"$decimalvalue"))
val df_trial: DataFrame = df_intermediate
else if (dataType == "varchar2")
print("varchar")
var DATA_LENGTH = (i \ "@DATA_LENGTH").text.toLowerCase().toInt;
var varcharvalue = "varchar(" + DATA_LENGTH + ")"
val df_intermediate =
df_trial.withColumn(s"$columnName",
col(s"$columnName").cast(s"$varcharvalue"))
val df_trial: DataFrame = df_intermediate
else if (dataType == "timestamp")
print("time")
val df_intermediate =
df_trial.withColumn(s"$columnName", col(s"$columnName").cast("timestamp"))
val df_trial: DataFrame = df_intermediate
);
scala apache-spark apache-spark-sql
add a comment |
I'm trying to typecast the columns in the data frame df_trial
which has all the columns as string, based on an XML file I'm trying to type cast each column.
val columnList = sXml \ "COLUMNS" "COLUMN"
val df_trial = sqlContext.createDataFrame(rowRDD, schema_allString)
columnList.foreach(i =>
var columnName = (i \ "@ID").text.toLowerCase()
var dataType = (i \ "@DATA_TYPE").text.toLowerCase()
if (dataType == "number")
print("number")
var DATA_PRECISION: Int = (i \ "@DATA_PRECISION").text.toLowerCase().toInt
var DATA_SCALE: Int = (i \ "@DATA_SCALE").text.toLowerCase().toInt;
var decimalvalue = "decimal(" + DATA_PRECISION + "," + DATA_SCALE + ")"
val df_intermediate: DataFrame =
df_trial.withColumn(s"$columnName",
col(s"$columnName").cast(s"$decimalvalue"))
val df_trial: DataFrame = df_intermediate
else if (dataType == "varchar2")
print("varchar")
var DATA_LENGTH = (i \ "@DATA_LENGTH").text.toLowerCase().toInt;
var varcharvalue = "varchar(" + DATA_LENGTH + ")"
val df_intermediate =
df_trial.withColumn(s"$columnName",
col(s"$columnName").cast(s"$varcharvalue"))
val df_trial: DataFrame = df_intermediate
else if (dataType == "timestamp")
print("time")
val df_intermediate =
df_trial.withColumn(s"$columnName", col(s"$columnName").cast("timestamp"))
val df_trial: DataFrame = df_intermediate
);
scala apache-spark apache-spark-sql
add a comment |
I'm trying to typecast the columns in the data frame df_trial
which has all the columns as string, based on an XML file I'm trying to type cast each column.
val columnList = sXml \ "COLUMNS" "COLUMN"
val df_trial = sqlContext.createDataFrame(rowRDD, schema_allString)
columnList.foreach(i =>
var columnName = (i \ "@ID").text.toLowerCase()
var dataType = (i \ "@DATA_TYPE").text.toLowerCase()
if (dataType == "number")
print("number")
var DATA_PRECISION: Int = (i \ "@DATA_PRECISION").text.toLowerCase().toInt
var DATA_SCALE: Int = (i \ "@DATA_SCALE").text.toLowerCase().toInt;
var decimalvalue = "decimal(" + DATA_PRECISION + "," + DATA_SCALE + ")"
val df_intermediate: DataFrame =
df_trial.withColumn(s"$columnName",
col(s"$columnName").cast(s"$decimalvalue"))
val df_trial: DataFrame = df_intermediate
else if (dataType == "varchar2")
print("varchar")
var DATA_LENGTH = (i \ "@DATA_LENGTH").text.toLowerCase().toInt;
var varcharvalue = "varchar(" + DATA_LENGTH + ")"
val df_intermediate =
df_trial.withColumn(s"$columnName",
col(s"$columnName").cast(s"$varcharvalue"))
val df_trial: DataFrame = df_intermediate
else if (dataType == "timestamp")
print("time")
val df_intermediate =
df_trial.withColumn(s"$columnName", col(s"$columnName").cast("timestamp"))
val df_trial: DataFrame = df_intermediate
);
scala apache-spark apache-spark-sql
I'm trying to typecast the columns in the data frame df_trial
which has all the columns as string, based on an XML file I'm trying to type cast each column.
val columnList = sXml \ "COLUMNS" "COLUMN"
val df_trial = sqlContext.createDataFrame(rowRDD, schema_allString)
columnList.foreach(i =>
var columnName = (i \ "@ID").text.toLowerCase()
var dataType = (i \ "@DATA_TYPE").text.toLowerCase()
if (dataType == "number")
print("number")
var DATA_PRECISION: Int = (i \ "@DATA_PRECISION").text.toLowerCase().toInt
var DATA_SCALE: Int = (i \ "@DATA_SCALE").text.toLowerCase().toInt;
var decimalvalue = "decimal(" + DATA_PRECISION + "," + DATA_SCALE + ")"
val df_intermediate: DataFrame =
df_trial.withColumn(s"$columnName",
col(s"$columnName").cast(s"$decimalvalue"))
val df_trial: DataFrame = df_intermediate
else if (dataType == "varchar2")
print("varchar")
var DATA_LENGTH = (i \ "@DATA_LENGTH").text.toLowerCase().toInt;
var varcharvalue = "varchar(" + DATA_LENGTH + ")"
val df_intermediate =
df_trial.withColumn(s"$columnName",
col(s"$columnName").cast(s"$varcharvalue"))
val df_trial: DataFrame = df_intermediate
else if (dataType == "timestamp")
print("time")
val df_intermediate =
df_trial.withColumn(s"$columnName", col(s"$columnName").cast("timestamp"))
val df_trial: DataFrame = df_intermediate
);
scala apache-spark apache-spark-sql
scala apache-spark apache-spark-sql
edited Nov 11 at 16:22
stealthyninja
9,475103947
9,475103947
asked Nov 11 at 10:07
Vamshi Manda
1
1
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
In each branch of the if-else you're using the values called df_trial
before you've defined them. You'll need to rearrange the code to define them first.
Note: the way you have it, the df_trial
at the very top is not being used. Depending on what you are trying to do, you may want to change the first df_trial
to a var
and remove the val
from the other usages. (This is probably still wrong since you will be overwriting the same variable multiple times as you loop over columnList
).
add a comment |
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%2f53247652%2fscala-forward-reference-extends-over-definition-of-value-dataframe%23new-answer', 'question_page');
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
In each branch of the if-else you're using the values called df_trial
before you've defined them. You'll need to rearrange the code to define them first.
Note: the way you have it, the df_trial
at the very top is not being used. Depending on what you are trying to do, you may want to change the first df_trial
to a var
and remove the val
from the other usages. (This is probably still wrong since you will be overwriting the same variable multiple times as you loop over columnList
).
add a comment |
In each branch of the if-else you're using the values called df_trial
before you've defined them. You'll need to rearrange the code to define them first.
Note: the way you have it, the df_trial
at the very top is not being used. Depending on what you are trying to do, you may want to change the first df_trial
to a var
and remove the val
from the other usages. (This is probably still wrong since you will be overwriting the same variable multiple times as you loop over columnList
).
add a comment |
In each branch of the if-else you're using the values called df_trial
before you've defined them. You'll need to rearrange the code to define them first.
Note: the way you have it, the df_trial
at the very top is not being used. Depending on what you are trying to do, you may want to change the first df_trial
to a var
and remove the val
from the other usages. (This is probably still wrong since you will be overwriting the same variable multiple times as you loop over columnList
).
In each branch of the if-else you're using the values called df_trial
before you've defined them. You'll need to rearrange the code to define them first.
Note: the way you have it, the df_trial
at the very top is not being used. Depending on what you are trying to do, you may want to change the first df_trial
to a var
and remove the val
from the other usages. (This is probably still wrong since you will be overwriting the same variable multiple times as you loop over columnList
).
edited Nov 12 at 6:23
answered Nov 12 at 5:30
Ryan
469615
469615
add a comment |
add a comment |
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.
Some of your past answers have not been well-received, and you're in danger of being blocked from answering.
Please pay close attention to the following guidance:
- 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%2f53247652%2fscala-forward-reference-extends-over-definition-of-value-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