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amount problem: Process runs with up to 99 pages but not larger amount
TobiasNehrig
Member Posts: 41 
Maven
Hi,
i've to analysis 2000 webpages. My test process with only 5 or up tu 99 pages to crawl runs fine. But when I change the crawler to crawl a larger number of pages like 100, 200, 1000 or 2000 I'got the error message: "Duplicate attribute name: id".
This is my process:
<?xml version="1.0" encoding="UTF-8"?><process version="8.0.001">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="8.0.001" expanded="true" name="Process">
<process expanded="true">
<operator activated="true" class="subprocess" compatibility="8.0.001" expanded="true" height="82" name="Crawler" width="90" x="45" y="289">
<process expanded="true">
<operator activated="true" class="web:crawl_web_modern" compatibility="7.3.000" expanded="true" height="68" name="Crawl Web" width="90" x="112" y="34">
<parameter key="url" value="http://www.spiegel.de"/>
<list key="crawling_rules">
<parameter key="store_with_matching_url" value=".+www.spiegel.+"/>
<parameter key="follow_link_with_matching_url" value=".+spiegel.+|.+de.+"/>
</list>
<parameter key="max_crawl_depth" value="10"/>
<parameter key="retrieve_as_html" value="true"/>
<parameter key="add_content_as_attribute" value="true"/>
<parameter key="max_pages" value="5"/>
<parameter key="max_page_size" value="500"/>
<parameter key="user_agent" value="Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:55.0) Gecko/20100101 Firefox/55.0"/>
</operator>
<operator activated="true" class="web:retrieve_webpages" compatibility="7.3.000" expanded="true" height="68" name="Get Pages" width="90" x="246" y="34">
<parameter key="link_attribute" value="Link"/>
<parameter key="page_attribute" value="link"/>
<parameter key="random_user_agent" value="true"/>
</operator>
<connect from_op="Crawl Web" from_port="example set" to_op="Get Pages" to_port="Example Set"/>
<connect from_op="Get Pages" from_port="Example Set" to_port="out 1"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="text:process_document_from_data" compatibility="7.5.000" expanded="true" height="82" name="Process Documents from Data" width="90" x="45" y="187">
<parameter key="keep_text" value="true"/>
<parameter key="data_management" value="memory-optimized"/>
<list key="specify_weights">
<parameter key="link" value="1.0"/>
</list>
<process expanded="true">
<operator activated="true" class="web:extract_html_text_content" compatibility="7.3.000" expanded="true" height="68" name="Extract Content" width="90" x="45" y="34">
<parameter key="minimum_text_block_length" value="2"/>
</operator>
<operator activated="true" class="text:tokenize" compatibility="7.5.000" expanded="true" height="68" name="Tokenize Token" width="90" x="179" y="34">
<parameter key="mode" value="linguistic tokens"/>
<parameter key="language" value="German"/>
</operator>
<operator activated="true" class="text:filter_tokens_by_content" compatibility="7.5.000" expanded="true" height="68" name="Filter Tokens a-zA-Z" width="90" x="313" y="34">
<parameter key="condition" value="matches"/>
<parameter key="regular_expression" value="[a-zA-Z]+"/>
</operator>
<operator activated="true" class="text:transform_cases" compatibility="7.5.000" expanded="true" height="68" name="Transform Cases" width="90" x="447" y="34"/>
<connect from_port="document" to_op="Extract Content" to_port="document"/>
<connect from_op="Extract Content" from_port="document" to_op="Tokenize Token" to_port="document"/>
<connect from_op="Tokenize Token" from_port="document" to_op="Filter Tokens a-zA-Z" to_port="document"/>
<connect from_op="Filter Tokens a-zA-Z" from_port="document" to_op="Transform Cases" to_port="document"/>
<connect from_op="Transform Cases" from_port="document" to_port="document 1"/>
<portSpacing port="source_document" spacing="0"/>
<portSpacing port="sink_document 1" spacing="0"/>
<portSpacing port="sink_document 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="multiply" compatibility="8.0.001" expanded="true" height="124" name="Process Doc2Data" width="90" x="45" y="34"/>
<operator activated="true" class="subprocess" compatibility="8.0.001" expanded="true" height="82" name="Filter tf-idf" width="90" x="179" y="85">
<process expanded="true">
<operator activated="true" class="transpose" compatibility="8.0.001" expanded="true" height="82" name="Ingress Transpose" width="90" x="45" y="34"/>
<operator activated="true" class="filter_example_range" compatibility="8.0.001" expanded="true" height="82" name="Filter Example Range" width="90" x="179" y="34">
<parameter key="first_example" value="1"/>
<parameter key="last_example" value="15"/>
<parameter key="invert_filter" value="true"/>
</operator>
<operator activated="true" class="filter_examples" compatibility="8.0.001" expanded="true" height="103" name="Filter Examples" width="90" x="313" y="34">
<parameter key="invert_filter" value="true"/>
<list key="filters_list">
<parameter key="filters_entry_key" value="id.equals.text"/>
</list>
</operator>
<operator activated="true" class="transpose" compatibility="8.0.001" expanded="true" height="82" name="tf-idf Transpose" width="90" x="447" y="34"/>
<connect from_port="in 1" to_op="Ingress Transpose" to_port="example set input"/>
<connect from_op="Ingress Transpose" from_port="example set output" to_op="Filter Example Range" to_port="example set input"/>
<connect from_op="Filter Example Range" from_port="example set output" to_op="Filter Examples" to_port="example set input"/>
<connect from_op="Filter Examples" from_port="example set output" to_op="tf-idf Transpose" to_port="example set input"/>
<connect from_op="tf-idf Transpose" from_port="example set output" to_port="out 1"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="subprocess" compatibility="8.0.001" expanded="true" height="124" name="Splitting" width="90" x="179" y="187">
<process expanded="true">
<operator activated="true" class="select_attributes" compatibility="8.0.001" expanded="true" height="82" name="Select Attributes" width="90" x="45" y="34">
<parameter key="attribute_filter_type" value="subset"/>
<parameter key="attributes" value="text"/>
<parameter key="include_special_attributes" value="true"/>
</operator>
<operator activated="true" class="generate_id" compatibility="8.0.001" expanded="true" height="82" name="Generate ID" width="90" x="45" y="136"/>
<operator activated="true" class="rename" compatibility="8.0.001" expanded="true" height="82" name="Rename ID" width="90" x="45" y="238">
<parameter key="old_name" value="id"/>
<parameter key="new_name" value="Document"/>
<list key="rename_additional_attributes"/>
</operator>
<operator activated="true" class="set_role" compatibility="8.0.001" expanded="true" height="82" name="Set Role" width="90" x="45" y="340">
<parameter key="attribute_name" value="text"/>
<parameter key="target_role" value="label"/>
<list key="set_additional_roles"/>
</operator>
<operator activated="true" class="rename" compatibility="8.0.001" expanded="true" height="82" name="Rename" width="90" x="179" y="34">
<parameter key="old_name" value="text"/>
<parameter key="new_name" value="word"/>
<list key="rename_additional_attributes"/>
</operator>
<operator activated="true" class="split" compatibility="8.0.001" expanded="true" height="82" name="Split" width="90" x="179" y="136">
<parameter key="attribute_filter_type" value="subset"/>
<parameter key="attributes" value="word"/>
<parameter key="include_special_attributes" value="true"/>
<parameter key="split_pattern" value="\s+"/>
</operator>
<operator activated="true" class="transpose" compatibility="8.0.001" expanded="true" height="82" name="Splitting Output" width="90" x="313" y="34"/>
<connect from_port="in 1" to_op="Select Attributes" to_port="example set input"/>
<connect from_op="Select Attributes" from_port="example set output" to_op="Generate ID" to_port="example set input"/>
<connect from_op="Generate ID" from_port="example set output" to_op="Rename ID" to_port="example set input"/>
<connect from_op="Rename ID" from_port="example set output" to_op="Set Role" to_port="example set input"/>
<connect from_op="Set Role" from_port="example set output" to_op="Rename" to_port="example set input"/>
<connect from_op="Rename" from_port="example set output" to_op="Split" to_port="example set input"/>
<connect from_op="Split" from_port="example set output" to_op="Splitting Output" to_port="example set input"/>
<connect from_op="Split" from_port="original" to_port="out 3"/>
<connect from_op="Splitting Output" from_port="example set output" to_port="out 1"/>
<connect from_op="Splitting Output" from_port="original" to_port="out 2"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
<portSpacing port="sink_out 3" spacing="0"/>
<portSpacing port="sink_out 4" spacing="0"/>
</process>
</operator>
<operator activated="true" class="subprocess" compatibility="8.0.001" expanded="true" height="187" name="Association" width="90" x="313" y="238">
<process expanded="true">
<operator activated="true" class="r_scripting:execute_r" compatibility="7.2.000" expanded="true" height="82" name="Generate Bigrams" width="90" x="45" y="34">
<parameter key="script" value="# rm_main is a mandatory function, # the number of arguments has to be the number of input ports (can be none) rm_main = function(data) { 	library(dplyr) 	library(tidytext) 	spon_bigrams <- data %>% 	 unnest_tokens(bigram, word, token = "ngrams", n = 2) 	print(spon_bigrams) return(list(spon_bigrams)) } "/>
</operator>
<operator activated="true" class="r_scripting:execute_r" compatibility="7.2.000" expanded="true" height="82" name="Seperate Bigrams" width="90" x="45" y="136">
<parameter key="script" value="# rm_main is a mandatory function, # the number of arguments has to be the number of input ports (can be none) rm_main = function(data) { 	library(dplyr) 	library(tidytext) 	library(tidyr) 	devided_bigrams <-data %>% 	 separate(bigram, c("word1", "word2"), sep = " ") 	 print(devided_bigrams) 	#counted_bigrams <- devided_bigrams %>% 	# count(word1, word2, sort = TRUE) # print(counted_bigrams) return(list(devided_bigrams)) } "/>
</operator>
<operator activated="true" class="multiply" compatibility="8.0.001" expanded="true" height="145" name="Seperated Bigrams" width="90" x="45" y="238"/>
<operator activated="true" class="r_scripting:execute_r" compatibility="7.2.000" expanded="true" height="82" name="Count Bigrams per Page" width="90" x="179" y="34">
<parameter key="script" value="rm_main = function(data) { 	library(dplyr) 	library(tidytext) 	library(tidyr) 	count_bigrams_per_page <- data %>% 	 count(Document, word1, word2, sort = TRUE) 	print(count_bigrams_per_page) 	counted_bigrams_per_page <- data.frame(count_bigrams_per_page) return(counted_bigrams_per_page) } "/>
</operator>
<operator activated="true" class="r_scripting:execute_r" compatibility="7.2.000" expanded="true" height="82" name="Count all Bigrams" width="90" x="179" y="187">
<parameter key="script" value="rm_main = function(data) { 	library(dplyr) 	library(tidytext) 	library(tidyr) 	count_bigrams <- data %>% 	 count(word1, word2, sort = TRUE) 	print(count_bigrams) 	counted_bigrams <- data.frame(count_bigrams) return(counted_bigrams) } "/>
</operator>
<operator activated="true" class="multiply" compatibility="8.0.001" expanded="true" height="103" name="Counted Bigrams per Page" width="90" x="313" y="34"/>
<operator activated="true" class="r_scripting:execute_r" compatibility="7.2.000" expanded="true" height="82" name="Filter Word 2" width="90" x="246" y="289">
<parameter key="script" value="rm_main = function(data) { 	library(dplyr) 	library(tidytext) 	library(tidyr) 	bigrams_filtered <- data %>% 	 #count(word1, word2, sort = TRUE) 	 filter(word2 == "spiegel") %>% 	 count(word1, word2, sort =TRUE) 	 print(bigrams_filtered) 	bigrams_filtered <- data.frame(bigrams_filtered) return(bigrams_filtered) } "/>
</operator>
<operator activated="true" class="multiply" compatibility="8.0.001" expanded="true" height="103" name="Multiply" width="90" x="246" y="391"/>
<operator activated="false" class="r_scripting:execute_r" compatibility="7.2.000" expanded="true" height="68" name="Visual (2)" width="90" x="514" y="391">
<parameter key="script" value="# not finished rm_main = function(data) { 	library(dplyr) 	library(tidytext) 	library(tidyr) library(igraph) bigram_graph <- data %>% #filter(n >= 6) %>% graph_from_data_frame print(bigram_graph) 	# bigram_graph <- data.frame(bigram_graph) 	library(ggraph) 	set.seed(2017) 	graph <- ggraph(bigram_graph, layout = "fr") + 	 geom_edge_link() + 	 geom_node_point() + 	 geom_node_text(aes(label = name), vjust = 1, hjust =1) 	setwd("/home/knecht") 	#write.csv(graph, '/home/knecht/filtergraphtest001') 	png(filename="filtergraphtest001") 	plot(graph) 	dev.off() 	 	 return(list(ggraph)) } "/>
</operator>
<operator activated="false" class="r_scripting:execute_r" compatibility="7.2.000" expanded="true" height="68" name="Visual" width="90" x="447" y="85">
<parameter key="script" value="# not finished rm_main = function(data) { 	library(dplyr) 	library(tidytext) 	library(tidyr) library(igraph) bigram_graph <- data %>% filter(n >= 6) %>% graph_from_data_frame print(bigram_graph) 	# bigram_graph <- data.frame(bigram_graph) 	library(ggraph) 	set.seed(2017) 	graph <- ggraph(bigram_graph, layout = "fr") + 	 geom_edge_link() + 	 geom_node_point() + 	 geom_node_text(aes(label = name), vjust = 1, hjust =1) 	setwd("/home/knecht") 	#write.csv(graph, '/home/knecht/graphtest001') 	png(filename="imagetest002.png") 	plot(graph) 	dev.off() 	 	 return(list(ggraph)) } "/>
</operator>
<connect from_port="in 1" to_op="Generate Bigrams" to_port="input 1"/>
<connect from_op="Generate Bigrams" from_port="output 1" to_op="Seperate Bigrams" to_port="input 1"/>
<connect from_op="Seperate Bigrams" from_port="output 1" to_op="Seperated Bigrams" to_port="input"/>
<connect from_op="Seperated Bigrams" from_port="output 1" to_port="out 1"/>
<connect from_op="Seperated Bigrams" from_port="output 2" to_op="Count Bigrams per Page" to_port="input 1"/>
<connect from_op="Seperated Bigrams" from_port="output 3" to_op="Count all Bigrams" to_port="input 1"/>
<connect from_op="Seperated Bigrams" from_port="output 4" to_op="Filter Word 2" to_port="input 1"/>
<connect from_op="Count Bigrams per Page" from_port="output 1" to_op="Counted Bigrams per Page" to_port="input"/>
<connect from_op="Count all Bigrams" from_port="output 1" to_port="out 3"/>
<connect from_op="Counted Bigrams per Page" from_port="output 1" to_port="out 2"/>
<connect from_op="Counted Bigrams per Page" from_port="output 2" to_port="out 4"/>
<connect from_op="Filter Word 2" from_port="output 1" to_op="Multiply" to_port="input"/>
<connect from_op="Multiply" from_port="output 1" to_port="out 5"/>
<connect from_op="Multiply" from_port="output 2" to_port="out 6"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
<portSpacing port="sink_out 3" spacing="0"/>
<portSpacing port="sink_out 4" spacing="0"/>
<portSpacing port="sink_out 5" spacing="0"/>
<portSpacing port="sink_out 6" spacing="0"/>
<portSpacing port="sink_out 7" spacing="0"/>
</process>
</operator>
<connect from_op="Crawler" from_port="out 1" to_op="Process Documents from Data" to_port="example set"/>
<connect from_op="Process Documents from Data" from_port="example set" to_op="Process Doc2Data" to_port="input"/>
<connect from_op="Process Doc2Data" from_port="output 1" to_port="result 1"/>
<connect from_op="Process Doc2Data" from_port="output 2" to_op="Filter tf-idf" to_port="in 1"/>
<connect from_op="Process Doc2Data" from_port="output 3" to_op="Splitting" to_port="in 1"/>
<connect from_op="Filter tf-idf" from_port="out 1" to_port="result 2"/>
<connect from_op="Splitting" from_port="out 1" to_port="result 3"/>
<connect from_op="Splitting" from_port="out 2" to_port="result 4"/>
<connect from_op="Splitting" from_port="out 3" to_op="Association" to_port="in 1"/>
<connect from_op="Association" from_port="out 1" to_port="result 5"/>
<connect from_op="Association" from_port="out 2" to_port="result 6"/>
<connect from_op="Association" from_port="out 3" to_port="result 7"/>
<connect from_op="Association" from_port="out 4" to_port="result 8"/>
<connect from_op="Association" from_port="out 5" to_port="result 9"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
<portSpacing port="sink_result 2" spacing="0"/>
<portSpacing port="sink_result 3" spacing="0"/>
<portSpacing port="sink_result 4" spacing="0"/>
<portSpacing port="sink_result 5" spacing="0"/>
<portSpacing port="sink_result 6" spacing="0"/>
<portSpacing port="sink_result 7" spacing="0"/>
<portSpacing port="sink_result 8" spacing="0"/>
<portSpacing port="sink_result 9" spacing="0"/>
<portSpacing port="sink_result 10" spacing="0"/>
</process>
</operator>
</process>
And this is the error message i've got:
Exception: java.lang.IllegalArgumentException
Message: Duplicate attribute name: id
Stack trace:
com.rapidminer.example.SimpleAttributes.register(SimpleAttributes.java:124)
com.rapidminer.example.SimpleAttributes.add(SimpleAttributes.java:203)
com.rapidminer.example.set.SimpleExampleSet.<init>(SimpleExampleSet.java:121)
com.rapidminer.example.utils.ExampleSetBuilder.build(ExampleSetBuilder.java:246)
com.rapidminer.operator.preprocessing.ExampleSetTranspose.apply(ExampleSetTranspose.java:165)
com.rapidminer.operator.AbstractExampleSetProcessing.doWork(AbstractExampleSetProcessing.java:117)
com.rapidminer.operator.Operator.execute(Operator.java:1004)
com.rapidminer.operator.execution.SimpleUnitExecutor.execute(SimpleUnitExecutor.java:77)
com.rapidminer.operator.ExecutionUnit$3.run(ExecutionUnit.java:812)
com.rapidminer.operator.ExecutionUnit$3.run(ExecutionUnit.java:807)
java.security.AccessController.doPrivileged(Native Method)
com.rapidminer.operator.ExecutionUnit.execute(ExecutionUnit.java:807)
com.rapidminer.operator.OperatorChain.doWork(OperatorChain.java:428)
com.rapidminer.operator.SimpleOperatorChain.doWork(SimpleOperatorChain.java:99)
com.rapidminer.operator.Operator.execute(Operator.java:1004)
com.rapidminer.operator.execution.SimpleUnitExecutor.execute(SimpleUnitExecutor.java:77)
com.rapidminer.operator.ExecutionUnit$3.run(ExecutionUnit.java:812)
com.rapidminer.operator.ExecutionUnit$3.run(ExecutionUnit.java:807)
java.security.AccessController.doPrivileged(Native Method)
com.rapidminer.operator.ExecutionUnit.execute(ExecutionUnit.java:807)
com.rapidminer.operator.OperatorChain.doWork(OperatorChain.java:428)
com.rapidminer.operator.Operator.execute(Operator.java:1004)
com.rapidminer.Process.execute(Process.java:1310)
com.rapidminer.Process.run(Process.java:1285)
com.rapidminer.Process.run(Process.java:1176)
com.rapidminer.Process.run(Process.java:1129)
com.rapidminer.Process.run(Process.java:1124)
com.rapidminer.Process.run(Process.java:1114)
com.rapidminer.gui.ProcessThread.run(ProcessThread.java:65)
Maybe here is someone who can help me.
Regards,
Tobias
0
Best Answer
-
TobiasNehrig
Member Posts: 41 Maven
Hi @sgenzer,
thanks for your message. With the breaking points I found the operator which caused the error, it is the tf-idf Transpose operator in the Filter tf-idf Subprocess. I tried to generate an ID in my Crawler and ran the process with 150 pages but the error is still there. When I disable tf-idf Transpose operator then the process work with 150 pages. Over night I'll test for 2000 pages. But still I don't understand why the process work with 5 pages but not with 100 or more when the tf-idf Transpose Operator is enable.
Regards,
Tobias
0
Answers
Hello @TobiasNehrig - hmm have you tried putting breakpoints along the way to see where the problem arises? There is no id attribute that is generated in your crawler subprocess so my hunch is that it is later down the workflow.
Scott
ok @TobiasNehrig - there are a few things here that I would recommend changing...
- you have no pruning set for your word vector creation and hence are creating a LOT of attributes. And this is only setting this to 5 pages. I cannot even imagine how many attributes you would have otherwise. You really need to set the pruning to get these attributes down to a reasonable number.
- you go through a lot of work to get rid of the metadata and text attribute (transpose, filter, etc..) but why not just uncheck the two boxes in Process Documents from Data? This would seem to avoid a whole lot of mess.
- if you're still getting collisions due to a duplicate attribute called "id", most likely you have a word vector called "id". I would use a Filter Tokens operator and get rid of that token.
Scott
hi @sgenzer,
thanks a lot. The process runs now by crawling max 2000 pages and deliver around 900 Example Set. I also followed your advise to clean up a bit so ein uncheck the "add meta information" and add prune, now it is clearer. The Text is my actual analysis goal.
regards
Tobias