Skip to main content



HTTP 400 Bad Request - Apache HTTP Client - HTTP POST JSON Message

 

For one of our projects, we faced issue where-in - 

  • We were utilizing Apache HTTP Client 4.5 and doing HTTP Post of JSON Message.
  • This was resulting HTTP Response as 
    • HTTP /1.1 400 Bad Request ...  
On analysis, we found that HTTP Post was failing just for Big JSON Files of size greater then 7 MB. So, initially we thought it to be a server side issue. 

But after further analysis we found that Unix CURL command was able to successfully POST message to API. Thus, we came to know that something was wrong with Scala (JAVA) client code that was using HTTP Client. 

Solution - 

  • We further updated the code and used java.net.{HttpURLConnection, URL} instead of org.apache.http.client.methods.{HttpPost} and it worked fine for us.

But, we were still buzzed with the problem why HTTPClient is not working. We tried using a proxy to capture HTTP Header and Body. So, as to compare difference between various user agents. 

  • And, we identified that Content-Length  for User-Agent : Apache-HttpClient/4.5 (Java/1.8.0._333) was little less then curl/7.83.1 and Java/1.8.0_333, which for us was 7783713 for prior and 7783726 for later. 
  • On further analysis, we found that code was using org.apache.http.entity.StringEntity - 
    • which by default uses ISO 8859-1 encoding (text/plain)
    • instead of UTF-8 (application/json)
UTF-8 is a multibyte encoding that represent any Unicode character. ISO 8859-1 is a single byte encoding that represents only first 256 Unicode characters.

  • We update our code to specify correct ContentType and it worked fine with HTTPClient as well.
    • new StringEntity(string, ContentType.APPLICATION_JSON)


Comments

Post a Comment

Popular posts

Unix Server ( Edge Node ) hangs when there are many jobs running on hadoop cluster started from Unix Edge Node.

  When a unix server or an edge node is running lots of jobs (like Spark, Hadoop, or custom batch processes), crashes happen. For example. For example a process might hit a segementation fault, memory issue or ay other runtime issue. By default, if ulimit -c is not 0, the OS will create core dump. Core dump are written to disk and can be very large, sometimes hundreds of MBs or even GBs per process. What we realized was that when multiple processes crash at the same time, the system suddenly tries to write core files to disk. This was leading to DisK I/O spikes. Thus, node was becoming unresponsive. This was also leading CPU spike because OS was handling crash logging. Setting "ulimit -c 0" disables core dumps. This way we lose ability to debug crashes via core dump But, kept production edge nodes stable. On most Linux systems, by default, "core dumps" are written in current working directory of the process that crashes. Linux allows you to change core dump file nam...
Post a Comment
Read more




VPN testing checklist

 To test: Is VPN active? Is it leaking? Does it look residential? Does it alter network fingerprints? Public IP Test (Basic Detection) - curl ipinfo.io DNS Leak Test - nslookup google.com MTU Test (Encapsulation Detection) - ping 8.8.8.8 -f -l 1472 TCP MSS Inspection - Use Wireshark and Look for SYN packets. Traceroute Path Test - tracert 8.8.8.8 WebRTC Leak Test - browserleaks.com/webrtc IPv6 Leak Test - test-ipv6.com Latency / Jitter Test - ping -n 50 8.8.8.8. VPN usually causes: More Jitters and Latency. Reverse DNS (PTR Record) - nslookup <your-public-ip> IP Reputation Check - Like most IP's from VPN Providers like Express VPN, etc. are blacklisted and all. Look for: Proxy/VPN classification, Hosting provider tagging
Post a Comment
Read more




Spark-JDBC connection with Oracle Fails - java.sql.SQLSyntaxErrorException: ORA-00903: invalid table name

  While connecting Spark with Oracle JDBC, one may observe exception like below -  spark.read.format("jdbc"). option("url", "jdbc:oracle:thin:@//oraclehost:1521/servicename"). option("dbtable", "mytable"). option("user", "myuser").option("driver", "oracle.jdbc.driver.OracleDriver") option("password", "mypassword"). load().write.parquet("/data/out") java.sql.SQLSyntaxErrorException: ORA-00903: invalid table name at oracle.jdbc.driver.T4CTTIoer.processError(T4CTTIoer.java:447) at oracle.jdbc.driver.T4CTTIoer.processError(T4CTTIoer.java:396) at oracle.jdbc.driver.T4C8Oall.processError(T4C8Oall.java:951) at oracle.jdbc.driver.T4CTTIfun.receive(T4CTTIfun.java:513) at oracle.jdbc.driver.T4CTTIfun.doRPC(T4CTTIfun.java:227) at oracle.jdbc.driver.T4C8Oall.doOALL(T4C8Oall.java:531) at oracle.jdbc.driver.T4CPreparedStatement.doOall8(T4CPreparedStatement.java:208) ...
Post a Comment
Read more




Agentic AI Development- Optimization- Bedrock Claude

Most of the models which you wish to invoke via AWS Bedrock, GPT, Google, etc, charges per token ( words/ characters ) For example -  A model like Claude is not a computer program that executes instructions. It is a statistical pattern matcher trained on text. It has no CPU, no memory, no ability to run code. It only predicts the next most likely token based on patterns it saw during training. But, some AI platforms give the model a sandboxed Python environment to actually execute code. Bedrock does have a Code Interpreter tool in Bedrock Agents — but that's a completely different setup- the overhead of setting it up just to decompress JSON makes zero sense when simply sending clean JSON is trivially easy. Easy Way To Estimate Your Cost- Step 1 — Measure your actual prompt size: Take your evidence JSON + instructions Paste into: https://platform.openai.com/tokenizer (OpenAI's tokenizer is close enough for estimation) It will tell you exact token count Step2 - Cost calculation C...
Post a Comment
Read more




Spring MongoDB Rest API not returning response in 90 seconds which is leading to client timeout

  We have Spring Boot  Rest API deployed in Kubernetes cluster which integrates with MongoDB to fetch the data.  MongoDB is fed with data by a real time Spark & NiFi job.  Our clients complained that for a request what they send they don't have response within 90 seconds. Consider it like an OMS ( Order ManagEment System).  On further analysis, we found that Spark & NiFi processing is happenning within 10 seconds after consuming response data from Kafka. Thus, initally out thought was that it due to delay from upstream to produce data in to Kafka.  Thankfully, our data had create / request  timestamp, and when response was received, and when response was inserted into MongoDB. Subtracting response insert time from request time seemed to be well within 90 seconds. But, still client did timeout on not seeing a response within 90 seconds. This led to confusion on our side.  But, then we realized it was due to Read Preference . We updated this...
Post a Comment
Read more