title: RAM issue with DASK and its from_pandas function
body: <p>i'm trying to use DASK package in Python 3.4 for avoid RAM problems with large datasets, but i've notice a problem.</p>
  
  <p>Using native fucntion "read_csv" i load big dataset into a dask dataframe using less than 150MB of RAM.</p>
  
  <p>The same dataset read with PANDAS DB Connection (using limit and offset options) and dask fuction"from_pandas" fill my ram uo to 500/750 MB.</p>
  
  <p>I can't undestand why this happens and i want to fix this issue.</p>
  
  <p>Here the code:</p>
  
  <pre><code>def read_sql(schema,tab,cond):
  
  sql_count="""Select count(*) from """+schema+"""."""+tab
  if (len(cond)&gt;0):
      sql_count+=""" where """+cond
  
  a=pd.read_sql_query(sql_count,conn)
  num_record=a['count'][0]
  
  volte=num_record//10000
  print(num_record)
  
  if(num_record%10000&gt;0):
      volte=volte+1
  
  sql_base="""Select * from """+schema+"""."""+tab
  if (len(cond)&gt;0):
      sql_base+=""" where """+cond
  sql_base+=""" limit 10000"""
  
  base=pd.read_sql_query(sql_base,conn)
  
  dataDask=dd.from_pandas(base, npartitions=None, chunksize=1000000)
  
  for i in range(1,volte):
      if(i%100==0):
          print(i)
      sql_query="""Select * from """+schema+"""."""+tab
      if (len(cond)&gt;0):
          sql_query+=""" where """+cond
      sql_query+=""" limit 10000 offset """+str(i*10000)
  
      a=pd.read_sql_query(sql_query,conn)
  
      b=dd.from_pandas(a , npartitions=None, chunksize=1000000)
  
      divisions = list(b.divisions)
      b.divisions = (None,)*len(divisions)
      dataDask=dataDask.append(b)
  
  return dataDask
  
  
  
  a=read_sql('schema','tabella','data&gt;\'2016-06-20\'')
  </code></pre>
  
  <p>Thanks for help me</p>
  
  <p>Waiting for news</p>